NTT Technical Review

December 2023 Vol. 21 No. 12
View from the TopHidehiro Tsukano, President & CEO, NTT Innovative Devices

Front-line Researchers


Hiroshi Yamaguchi, NTT Fellow, NTT Basic Research Laboratories

Rising ResearchersTomonori Fujita, Distinguished Researcher, NTT Software Innovation CenterFeature Articles: Toward More Robust Networks
Operation to Achieve Robust Networks

Technologies for Promptly Understanding Network Conditions When Large-scale System
Failure Occurs

Network Reliability Design and Control Technology for Robust Networks



NW-AI Self-evolving Framework for Fault-tolerant Robust Networks

Regular Articles

Human-behavior-understanding Engine: Video-recognition AI Library for Understanding
Human Behavior



Low-latency Function-dedicated Network Providing Sustained and Stable Services

Global Standardization Activities


Report on the Second Plenary Meeting of ITU-T SG2 Standardization of Telecommunication
Numbering

Practical Field Information about Telecommunication Technologies
Case Studies in 50-bit/s Leased Lines: Modem Communication Failure at Earth-return Circuitand the Cause of Failure to Replace Metallic Transmission Line with Optical Cable

External Awards

View from the Top

Accumulate Successful Experiences
and Cultivate a Can-do Attitude to
Becoming a Market-oriented
Company
Hidehiro Tsukano
President & CEO, NTT Innovative Devices
Abstract

NTT Innovative Devices has begun its journey as a manufacturer specialized in photonics-electronics convergence devices. By designing, developing, manufacturing, and selling strategic devices that make up the core
infrastructure of the Innovative Optical and Wireless Network (IOWN), thecompany strives to enable high-speed, large-capacity communications
through innovative technologies focused on photonics and contribute to
reducing power consumption and building a sustainable society in accordance with the IOWN concept. We asked Hidehiro Tsukano, president &CEO, NTT Innovative Devices, about the company’s business and his
mindset as a top executive.
Keywords: photonics-electronics convergence device, IOWN, market-oriented mindset

Manufacturer specialized in design, development,
manufacturing, and sales of photonics-electronics
convergence devices—Congratulations on the establishment of NTT
Innovative Devices. You serve as the company’s
president & CEO as well as the head of NTT IOWN
Integrated Innovation Center, right?
Since I became the head of NTT IOWN Integrated
Innovation Center in 2021, I have realized the powerof NTT’s research and development (R&D) and theimportance of the Center’s mission through discussions with researchers and reports on research results.
At the time of NTT IOWN Integrated Innovation
Center was established, NTT was taking concrete
steps toward implementation of the Innovative
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Vol. 21 No. 12 Dec. 2023

Optical and Wireless Network (IOWN), which wasannounced two years before. In August 2023, bymerging NTT Electronics, which was an existing
operating company, we established a new company,
NTT Innovative Devices. As the head of the newcompany, I have a renewed sense of the heavy
responsibility of being in a position to actualize
IOWN through the development and commercialization of photonics-electronics convergence devices
that form the core of IOWN.
To provide such devices, we are striving to organize
related technologies and processes, streamline theprocess pipeline, and prepare the environment tomanufacture the devices within two years. In terms ofspeed, we hope to be able to reap the results of thoseactions as a business in our third year. In the NTT
Group, which employs 330,000 people and generates
1View from the Top

annual sales of 13 trillion yen, we are in the very
unique position of being a device company with 1100
employees and consolidated annual sales of 44.3 billion yen and having a manufacturing department.
—Could you tell us about the specific business andvision of NTT Innovative Devices?
We are a manufacturer specialized in photonicselectronics convergence devices with a full scope offunctions, such as design, development, manufacturing, and sales. Our predecessor, NTT Electronics,
provided its customers with core components for
medium- and long-haul optical transmission, such as
coherent digital signal processors and optical transceivers, and focused on telecommunications carriers
as its main end customer. Such products had been
manufactured by using technology for fabricating
optical devices on silicon substrates using microfabrication technology for large-scale integration circuits (LSIs) and technology for integrating these
optical devices and digital coherent devices for
medium- and long-haul optical transmission in asingle package.
After becoming NTT Innovative Devices, we want
to expand our products into the field of computing—which we consider to be a new market. For the traditional field of medium- to long-haul optical transmission, we will continue to evolve our products for
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Vol. 21 No. 12 Dec. 2023

even-higher-capacity and longer-haul optical transmission. We are also accelerating the development of
products for low-power and short-haul optical transmission. We plan to unveil these products at Expo
2025 Osaka, Kansai, Japan.
Our medium-term goal is to enable photonicselectronics convergence devices to be mounted fromon the edge of chassis to the edge of boards for highcapacity and short-haul optical transmission such as
in clusters and between servers and storage in datacenters. Our long-term goal is to develop chiplets by
reducing the size and thickness of photonics-electronics convergence devices and by mounting LSIs
and optical devices on the same substrate. We aremounting such chiplets from the edge of systemboards to the edge of a semiconductor chip on boards.
By embedding such chiplets on the edge of silicondies inside semiconductor packages, we aim to createa market in which chiplets are built into logic LSI
packages such as various processing units called
xPUs. We hope that in the future, optical chiplets will
be used in various areas so that the world’s estimated
9.5 billion people in 2050 will be able to enjoy thebenefits of the power of photonics—including low
power consumption, low latency, and high-transmission-capacity communications.

2View from the Top

Actualizing strategic devices for building the core
infrastructure of IOWN—You have a clear vision. What exactly is the missionof your company? Could you tell me financial goals?
Our mission is to actualize strategic devices inbuilding the core infrastructure of IOWN and reduce
power consumption, which is a significant goal of the
NTT Group for contributing to society.
The deployment target of IOWN covers a vast area
and consists of four layers. The first layer is composed of semiconductor devices, and the second layer
is composed of elements of the core infrastructurethat enables the IOWN world to be created using thefirst-layer devices. This layer is equivalent to the current “box”-type server-oriented architecture consisting of network interface cards and various computing
resources. The third layer is network applications,and the top (fourth) layer is composed of solution
services and business for providing added value toexternal customers.
Our primary goal is to increase the value of the
fourth layer. To that end, it is important to accelerate
the development of devices for low-power and shorthaul optical transmission while pursuing high-capacity transmission by increasing performance of thefirst-layer devices.

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Vol. 21 No. 12 Dec. 2023

In terms of financial goals, we are aiming forannual sales of 100 billion yen. Since the consolidated annual sales of NTT Electronics were approximately 40 billion yen, our first hurdle will be doubling that amount. How quickly we can achieve thatgoal depends on how quickly we can accelerate
product development, on which we are working hard.
—Annual sales of 100 billion yen are eagerly anticipated. We’d like to hear about your specific strategies
for achieving the goal.
Ultra-small and thin chiplets mean that photonicselectronics convergence devices are structurally
closer to semiconductors than to modules. We cantherefore say that our direct customers are the manufacturers who use these semiconductors. In addition
to Japan, the main sales region is North America, followed by Europe, where we were able to tap into the
French market. We also have access to Asia.
To succeed in this market, we first must enable
photonics-electronics convergence chiplets to be
introduced in a wider range of computing areas; however, this will not be possible without first and foremost a large volume of devices. Therefore, it is necessary to establish mass-production technology to
improve the ability to supply a large volume ofdevices and reduce costs.

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View from the Top

Regarding our position in this market, we are at theleading edge compared with other players in terms oftechnology since our products are based on the photonics-related technologies that NTT R&D has developed and accumulated over the past 20 to 30 years.
However, even though we have cutting-edge technology and excellent knowledge of cutting-edge products, we are clearly inferior to our competitors interms of our business approach, including our sales
capabilities. This situation is somewhat understandable because we are a technology- and product-oriented company where products are developed
through technology transfer of research results. In anutshell, I want to rethink the business of NTT
Innovative Devices from a “business” perspective
and develop it with a market-oriented mindset. I’m
now thoroughly reviewing all operations from a business perspective while drawing on my 26 years ofexperience at Fujitsu and giving direct instructions toeach person in charge.
When the technologies and ideas created inresearch laboratories entered the development phaseand were provided to the group’s operating companies, if they were viewed from a business perspective
as a service or product, they often needed to be
adjusted to meet market needs or reduce costs.
However, they could not be modified and brought tomarket because the operating companies did not havea manufacturing department. Since NTT Innovative
Devices has a manufacturing department, we believe
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that we can considerably improve the business practices that have been adopted since the days of NTT
Electronics by establishing the process of tailoringproducts backcast from market needs through discussions at each point from a business perspective.
Review traditional business processes from amarket-oriented perspective—It seems that the presence of NTT Innovative
Devices will change drastically from what it has
been. You mentioned earlier that the company will be
reorganized and streamlined within two years. Whatis the meaning of the time frame of this reorganization?
I want to embed ideas based on the knowledge andexperience I have gained during my previous job at
Fujitsu and as the head of NTT IOWN Integrated
Innovation Center into NTT Innovative Devices as
quickly and deeply as possible. I wanted to change
what we could in one year so that we could start reaping the benefits in the second year. However, in thesituation in which I alone will be trying to embed myknowledge and experience into the company culture,
I am not sure how quickly I can change the productoriented mindset to a market-oriented mindset.
It takes a lot of energy to change what has becomea custom; thus, I sometimes wonder if I’m tired ofembedding my ideas after a year. We humans have a4

View from the Top

tendency to give up on something that is too difficult,so I fear that I might. Therefore, I have no choice but
to accomplish the reorganization in the short term.
That is, I want to achieve structural reforms in the
two-year range and see results in the third year. This
challenge can be considered a kind of self-evaluation.
I started communicating my ideas after August 1,
2023, when the company was established, and by theend of September, 95% of the company had become
what I had envisioned. That was scarily fast. I believethat it is important to be able to feel that the positionof NTT Innovative Devices has changed and to accumulate successful experiences that show that we cando anything if we try. Naturally, not everything goessmoothly, and sometimes things don’t go as planned.
We don’t want to spend too much time trying toescape from such a situation, but I think we have no
choice but to persevere. In any case, I want to work
hard to push for change.
I’m driven to work in this manner because I feelthat the moment I stop, I will degenerate. I want topursue what I like at my own speed, and I don’t want
to be left behind by the world.
—Finally, would you tell us what it is to be a top
executive and what type of a top executive you would
like to be? And please give us your message to NTT
researchers, the company’s employees, customers,
and partners.
To put it simply, no one is behind the top executive.
The president takes responsibility for anything that
happens in business, be it good or bad. In a sense, thetop executive is a solitary entity. If the top executive
does not say to the employees, “Let’s change, let’s dothis,” those who think it’s fine to continue as is will
not change. The size of the organization and its social
responsibilities may vary from company to company,
but from the perspective of the president’s job, I
believe that they are essentially the same entity. In
other words, the person at the top must make decisions and take responsibility for such decisions. And
choices and decisions should be made as quickly as
possible.
I believe that NTT Innovative Devices should not
rely on the safety net that is being a member of the
NTT Group. I want to build a mindset that allows
NTT Innovative Devices to operate as an independent
device company. NTT has published a roadmap of

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photonics-electronics convergence devices to 2032,
when the fifth-generation products of such devices
will be released. The announcement of the roadmap
demonstrates NTT’s confidence, and companies havecome together to hear about materials, services, etc.
We have also been able to start creating an industrial
ecosystem and see the reactions of our competitors ina manner that has allowed us to read the trends in themarket.
As I mentioned at the beginning, we plan toannounce the third generation of NTT Innovative
Devices products in 2025. NTT R&D departments
deal with wide-ranging fields and has a discerning
eye in many different areas. We have streamlined theprocess pipeline, which enabled us to shorten thetime to introduce superior technologies and products
to society by about three or four years per generation.
We hope that our customers and partners will confirm our clearly stated goals in the roadmap and bring
their ideas of how they would like to engage with our
products and services. Neither the value chain nor the
supply chain can be established by one company
alone. We want to make the chain—which used to bethin and long like a spider’s thread—into something
thicker, stronger, and more flexible.

Interviewee profile
Career highlights
Hidehiro Tsukano joined Fujitsu Limited in
1981, where he worked in the purchasing department, focusing on semiconductors. In his careerat Fujitsu, he became head of Corporate Planningand Business Strategy Office in 2009 and representative director, senior executive vice president, and chief financial officer in 2017. He has
also served as chief human officer and chief
strategy officer, in charge of all departments as
assistant to the president. In 2019, he became
vice chairman of the company. After working
as an advisor to NTT Advanced Technology
Corporation and senior advisor in the Research andDevelopment Planning Department of NTT in
2020, he has been senior vice president, head of
NTT IOWN Integrated Innovation Center since2021 and president & CEO of NTT Innovative
Devices Corporation since August 2023.

5

Front-line Researchers

Combining Nanomechanics andUltrahigh-speed Magnophononic
Technology Makes It Possible to Use
Phonon Signals as Information
Carrier Other Than Electrical and
Optical Signals
Hiroshi Yamaguchi
NTT Fellow, NTT Basic ResearchLaboratories
Abstract

The Innovative Optical and Wireless Network (IOWN) willtransform the information carriers not only in the transmission
lines but also in the internal circuits of computers from electricalsignals to optical signals. The key to achieving this is an opticaltransistor, which can be fabricated using photonic crystals that canconfine and control the light within devices. A completely different approach to device technology, i.e., using acoustic waves(elastic waves) in the gigahertz frequency range, has also been
extensively studied. As a fundamental research topic, nanomechanics is being researched to enable low-power information processing and ultra-sensitive signal detection by controlling the propagation of acoustic waves in the nanoscale domain. One of the techniques
studied in nanomechanics is the use of a nanoscale artificial structure called phononic crystal, which
confines and controls the acoustic waves in a device. We interviewed Hiroshi Yamaguchi, an NTT Fellow at NTT Basic Research Laboratories, who is engaged in research on nanomechanics, about the current status and future prospects of his research, changes in the circumstances surrounding the basic
research, and his thoughts on how researchers should conduct their research with those changes in mind.
Keywords: nanomechanics, nonlinear nanomechanical device, magnophononic technology

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Front-line Researchers

Fabricate new functional devices by using
nanomechanics and ultrahigh-speed
magnophononic technology—Would you tell us about the research you are currently working on?
I have been researching nanomechanics for morethan 10 years. Optical devices and semiconductor
devices exploit the physical phenomena of light andelectrons, whereas nanomechanics uses the mechanical properties of acoustic vibrations in microstructures. An acoustic vibration is something like thesound transmitted to the end of the desk when you tap
the other edge of a desk or the vibration continuing at
a fixed pitch when you tap a tuning fork. As electric
devices, quartz crystals use the acoustic vibrations aswatches and computer clocks to keep time. Embedding a slice (thin film) of quartz crystal into a circuit
causes the crystal to vibrate at a very precise frequency. This phenomenon is applied to provide
highly accurate frequency signals for many numbersof watches, computers, and other types of electronic
devices.
Microelectromechanical systems (MEMS) havebeen extensively studied to use such elastic acoustic
vibrations in electronic devices, and nanomechanics
can be called the next-generation technology ofMEMS. Using the nonlinearity of the elastic properties or combining it with quantum-device technology
enables the fabrication of devices with functions notpossible with MEMS (see Table 1).
“Nonlinearity,” which may be an unfamiliar term,means that the output of the device is not proportional to the input. In fact, semiconductor devices,such as diodes and transistors, have demonstrated avariety of functions through their nonlinearities.
These functions cannot be provided by devices withlinear characteristics such as inductors, capacitors,
and resistors. For example, the current flows througha resistor in proportion to the applied voltage. With adiode, however, the current and applied voltage are
not proportional. For transistors, this nonlinear characteristic changes in accordance with the voltage orcurrent applied to the electrode. For acoustic vibrations, this nonlinear characteristic corresponds to thefact that the magnitude of vibration is not proportional to the force applied to the material, and theeffect of such nonlinearity becomes more pronouncedwith miniaturization of the device. By exploiting
such nonlinear characteristics, my research colleagues and I aim to create nonlinear nanomechanical
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devices with innovative functions similar to those ofdiodes and transistors.
Integration of nanomechanics with quantum-device
technology is expected to enable the fabrication of
new functional devices. When a nonlinear nanomechanical device is combined with quantum dots, forexample, it is possible to detect extremely fine vibrations equivalent to the diameter of an atomic nucleus.
By incorporating semiconductor lasers and otherdevices, a nonlinear nanomechanical device can control optical signals. These applications require ultrahigh-speed operation at frequencies above 1 gigahertz (GHz).
We have been focusing on phonon hybrid devices,which combine quantum devices and nanomechanics. As the smallest units of acoustic vibration, phonons are attracting attention through their integration
with quantum technology. From 2015 to 2019, I was
the principal investigator of a research project called“Phonon hybrid quantum science” in a research areaof the “Science of hybrid quantum systems” in the
Grant-in-Aid for Scientific Research (KAKENHI)
and explored quantum technology using phonons. In
this project, co-investigators and I succeeded inincorporating a new function into nanomechanics bycombining phonon devices with semiconductor
quantum structures. We are currently investigating
new phonon hybrid devices as advanced technologies
that integrate not only semiconductors but also othermaterial systems such as magnetic materials, rareearth elements, and solutions.
For example, we have been studying the phononic
crystal, an ultra-fine artificial structure that confines
acoustic vibration. This is the acoustic analogue ofphononic crystals, which confines light waves in an
artificial structure. By combining the phononic crystal with ferromagnetic materials, we have recently
succeeded in demonstrating a phenomenon called
ferromagnetic resonance in a region 10,000 times
smaller than that possible with conventional methods. Ferromagnetic resonance is a phenomenon bywhich magnetic materials are sensitive to alternating
current signals of a fixed frequency and expected tobe applied to ultra-sensitive magnetic sensors andinformation processing using magnetic materials.
These applications are examples of new hybrid
devices combining nanomechanics and magnetism.
We also fabricated an acoustic resonator that operates
at ultrahigh-frequency ranges (30 GHz or higher)using a nitride-semiconductor single-crystal thinfilm (Fig. 1) [1]. We believe that this achievement
will enable ultrafast operation by combining various
7

Front-line Researchers

Table 1. Comparison of devices and functions concerning electronics and micro/nanomechanics.
Nonlinear device

Linear device

Electronics

Quantum device

2-terminal device

3-terminal device

Inductor
Capacitor
Resistor

DiodeTransistor

Quantum bit
Quantum memory

Tuner
FilterDemodulator
RectifierAmplifier/switch
Memory/logic

Quantum computing
Quantum sensing

Resonator
Micro/nanomechanics

High-frequency filter
Sensor/gyro
Microphone

Future research targets

AlN (aluminum nitride)
single-crystal thin film

Top electrodeS11 (dB)

−2.6
AlN
SiC

Resonance
characteristics

−2.7
−2.8
−2.9
40.00

SiC

40.10

40.20

Frequency (GHz)

Fig. 1. A coustic resonator (fabricated using a nitride-semiconductor single-crystal thin film) and its resonance characteristics[1].

materials and quantum structures as hybrid devices.
We also believe that this will potentially impact thedevelopment of mobile technologies such as highfrequency microwave filters.
—I heard that you have launched a new KAKENHI
project.
In April 2023, we started a joint research projectwith the University of Tokyo on the theme of “Ultrahigh-speed magnophononic resonator devices,”
which is a KAKENHI project administered by Japan
Society for the Promotion of Science. Memory incomputers stores states of 0 and 1 in accordance withwhether electrons are accumulated in a specific areaof a semiconductor; in contrast, magnetoresistive
random-access memory (MRAM) stores informationin an electronic device by assigning the N (north) andS (south) poles of a magnetic material (instead of asemiconductor) as 0 and 1. Ultrahigh-speed magnophononic technology combines technology thatNTT Technical Review

Vol. 21 No. 12 Dec. 2023

uses magnetic materials, such as MRAM, and technology that handles acoustic vibrations (Fig. 2) [2].
Ferromagnetic materials enable devices to operate
at extremely high frequencies, as high as 100 GHz,and have non-volatility, which allows them to maintain such a state. By combining ferromagnetic materials with phononic devices, ultrafast hybrid devices
that harness the non-volatility of ferromagnetic materials can be fabricated. For example, programmable
operation for high-frequency signal processing may
be possible by using such hybrid devices in sensors
and timing devices used in mobile terminals. For
conventional electronic circuits, as frequency
increases, electrical signals leak out as electromagnetic waves, which cause strong interference between
circuits. If this interference can be avoided using
magnophononic technology, phonon signals could be
used as a new information carrier to replace electricalsignals. If magnetic sensing with sensitivity comparable to that of superconducting quantum interference
devices, which require cryogenic temperatures, can8

Front-line Researchers

Spintronics technology

Phononic (acoustic) technology
Acoustic
resonance
GHz acoustic
waves(phonons)

Hybrid operation
through strong
coupling

Propagation of spin precession

GHz spin waves (magnons)

Fig. 2. Conceptual diagram of ultrahigh-speed magnophononic technology [2].

be achieved at room temperature, it could be used in
medical devices such as magnetoencephalographs.
Application of magnophononic devices as micronsized ultra-small high-frequency antennas has also
been proposed, and such devices could significantly
change the performance of mobile terminals. While
keeping these applications in mind, we also want topursue fundamental research on physical properties,
such as the interaction between magnetism and vibration, which still has many aspects that have not been
elucidated.
Breaking away from an inward-looking mindset
and building research collaboration—The circumstances surrounding Japan’s basic
research are changing drastically, right?
I sense three major changes. First, connections withoverseas researchers have become weaker. International conferences and meetings have shifted toonline due to the COVID-19 pandemic, but the effectiveness of face-to-face contact and discussion at inperson conferences cannot be replicated online. I
have given three presentations at international conferences outside Japan since the beginning of 2023,
and even now that the classification of COVID-19
has been downgraded to the same level as seasonal
influenza in Japan, I feel that the number of Japanese
researchers participating in international conferences
and other events is smaller than that before the pandemic. The number of young researchers who travel
abroad is particularly low. I suspect that the reason
for that is the remaining high level of vigilanceagainst COVID-19 infection and increased airfares
due to the rising cost of fuel and the longer flights dueto the inability to transit over Siberia. The moreadvanced research becomes, the more difficult it
becomes for a single group to conduct it, so researchexchanges with researchers inside and outside the
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country have become essential. In such cases, personal connections with overseas researchers can be ofgreat help. Internationalization of young humanresources is an important issue facing various
research fields, and sending young researchers
abroad to participate in joint research is crucial inbasic research. Japan is said to be inward-looking
these days, I think we should increase our contacts
with overseas researchers and promote internationalization and diversification of our research.
The second major change is the remarkableadvancement of other Asian countries. China, especially, has a large population and an order-of-magnitude-more funding for research. A simple proportional calculation based on these factors would indicate that the numbers of talented researchers andworld-class laboratories are overwhelmingly large.
This is especially true in new research fields.
Although I believe Japan and NTT are still in a position to lead the world in optical and semiconductor
technologies, we cannot let our guard down. I thinkthat we will need to further improve collaborative
research and research processes, including the selection of fields and themes, and we are currently investigating ways to make those improvements.
The third major change is the emergence of generative artificial intelligence (AI). Many tasks, such as
writing abstracts and introductions of papers andautomatically creating programs for experimental
apparatus, can be made more efficient by using generative AI. This capability can cause changes in the
research processes that I mentioned above. While
researchers in some countries are actively promoting
the use of generative AI, issues concerning copyright,
credibility of research results, and the literacy ofusers are being discussed in various fields. How toapply generative AI to our research is a major challenge.

9Front-line Researchers

Recommendation for “detour research”—Please tell us what you keep in mind as a researcher.
In my previous interview, I emphasized threepoints: (i) setting goals that are different from others,(ii) while focusing on your own strengths, pivoting
into other fields, and (iii) extending the antenna highand wide to obtain new and useful information. I’ll
discuss the following three additional points as well
as further explain the above three points based on myresearch style.
In a new field of basic research, obtaining results at
an early stage greatly influences subsequent attention, so many researchers focus on research themesthat have a clear logical structure and precise idea ofwhat needs to be done. However, such research
themes are easily noticed by other researchers, socompetition between researchers is fierce. Therefore,
I recommended setting goals that are different fromothers in the previous interview. If a theme of interest
comes up during the course of research, I think it isimportant to take a detour to that theme while leaving
the initial goal as it is. If the theme is likely to have aneven greater impact on your field of research, you
should boldly change your goal in that direction. If
taking a detour does not seem to work, you just returnto the initial goal. While it is important to stick toyour initial goal, it is also important to be flexible inchanging the theme with a freer mindset.
The practice of give and take is often taught when
researchers are collaborating, whether it is joint
research, activities concerning academic societies, or
sharing research within a team. Many people tend to
think of taking exactly 50%, and some take as muchas possible. However, your partner will be thinking inthe same way, so a struggle will occur between you
and them. Therefore, if you think about giving andtaking at a ratio of 7:3, you will make your partner
think that it is highly beneficial to work with you, andthe collaboration will go well. This is a lesson frommy former senior. Even if you think the give-and-takeratio is 7:3, it is often 6:4 when you actually try it. It
could also be reversed to a ratio of 4:6. The important
point is how to create the conditions for a positivecommitment from both partners.
I believe that there are no higher or lower ranks inthe thoughts and ideas of each researcher, especiallyregarding basic research; that is, all researchers
should be equal regardless of whether they are inmanagerial or non-managerial positions. The above
7:3 give-and-take practice should also be applied
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between managers and non-managers. Even if you
are a manager, it is important to respect the otherperson’s idea and make decisions on the basis of correct knowledge and logic. Therefore, a frankexchange of information will occur and good ideas
will emerge. This attitude is also in line with themotto of Shoji Yoshida, the first director of NTT
Basic Research Laboratories, “All members of NTT
Basic Research Laboratories share the common principle of acting voluntarily and proactively withstrong will and humility without falling into the trapof self-righteousness.” With that in mind, Director
Yoshida chose the word “will” as the attitude requiredof researchers at the laboratories. I do not think theimportance of that attitude has changed, even after
nearly 40 years.
Streamlining the research process and valuingwhat you have
—What is your message to younger researchers?
When you start your first step as corporate researchers, many of you will be involved in research in different fields from what you specialized in when you
were students. When I was a student, I researchedtheoretical particle physics; however, when I joined
NTT, I was involved in the completely different fieldof experimental research on semiconductors. At thattime, I was almost an amateur researcher on semiconductors, and I had a sinking feeling that the knowledge I had worked so hard to accumulate as a student
would be completely meaningless. However, over theyears, I have found that I can make surprisingly gooduse of my knowledge from my student days in myresearch on nanomechanics. It may be that my pastexpertise served as a potential trigger for me to startresearching nanomechanics. This outcome is true not
only for scientific expertise but also for all past experiences such as club activities and volunteer work. I
think that people who have made great efforts in thepast will be more inclined to try to make use of thatexperience, and that is why they made the effort to doso. However, when they enter a new environment,
they often find that their experience does not immediately translate well to the new environment. If thisis the case, you should not immediately reject thatenvironment; instead, it is important to plan yourlives with the attitude that opportunities in which you
can make use of the experience will surely arise.
The environment in which research is conducted
has changed dramatically since the words “work-style10

Front-line Researchers

reform” and “work-life balance” became commonplace. In addition, the “universalization of information,” allowing anyone to retrieve a variety of information with a single keyboard operation by asking asearch engine or AI, is progressing. In other words,
we are entering an era in which anyone can easily dowhat was previously only possible for experienced
researchers. To conduct highly original research inthis environment, it has become even more important
to work efficiently by focusing on what you are bestat. It is therefore necessary for researchers to reevaluate where they are going to compete and for
managers and non-managers to respect the individuality of each researcher, rather than imposing a uniform methodology onto them.
References
[1]

[2]

D. Hatanaka, M. Asano, H. Okamoto, and H. Yamaguchi, “Phononic
Crystal Cavity Magnomechanics,” Phys. Rev. Applied, Vol. 19,054071, May 2023. https://doi.org/10.1103/PhysRevApplied.
19.054071

Interviewee profile
Hiroshi Yamaguchi received a B.S. and M.S. inphysics and Ph.D. in engineering from Osaka
University in 1984, 1986, and 1993. He joined
NTT Basic Research Laboratories in 1986. His
current interests are in micro/nanomechanicaldevices using semiconductor heterostructures.
He is a fellow of the Institute of Physics andJapan Society of Applied Physics and a memberof the American Physical Society, the PhysicalSociety of Japan, and the Institute of Electricaland Electronics Engineers.

M. Kurosu, D. Hatanaka, R. Ohta, H. Yamaguchi, Y. Taniyasu, and H.
Okamoto, “Impedance-matched High-overtone Bulk Acoustic Resonator,” Appl. Phys. Lett., Vol. 122, 122201, Mar. 2023. https://doi.
org/10.1063/5.0141405

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Vol. 21 No. 12 Dec. 2023

11

Rising Researchers

Creating a New Ecosystem with
Highly Reliable System-software
Technology in a Way that Contributes
Globally
Tomonori Fujita
Distinguished Researcher, NTT Software
Innovation Center
Abstract

Today, with the spread of the Internet and the integration of
information and communication technology into our daily lives,the demand for reliable software has increased dramatically. The
C language, which is currently the dominant language for software development in fields requiring high performance, offers
flexibility and freedom in manipulating hardware; however, it
faces concerns that simple mistakes by the software developer canlead to bugs and security risks. Under those circumstances, programming technologies for developing software that satisfies therequirements of the modern era—namely, high performance and reliability—are demanded, and efforts
to develop a new programming language to replace C are underway. In this issue, we interviewed Distinguished Researcher Tomonori Fujita, who is engaged in research on “highly reliable system-software
technology.”
Keywords: system software, Rust, BGP daemon

Creating new software with Rust—which
combines high performance and security—What is your approach to “highly reliable systemsoftware technology”?
The “highly reliable system-software technology”
that I am researching aims to ensure that system software that controls hardware can withstand hardware
failures and network attacks and continue to operate
as expected. Achieving that aim requires a variety ofbasic technologies, and I’m currently working on
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Vol. 21 No. 12 Dec. 2023

avoiding software problems that can lead to systemoutages and external attacks. In particular, I’m aiming to create high-performance system software byusing Rust—instead of the mainstream C language—as the programming language for developing thatsystem software because Rust offers an advantageous
safety feature; namely, it can prevent errors by developers.
The background to my research is the increased
demand for software with the reliability to support
today’s Internet-enabled world. In the 1990s, whenthe Internet was just becoming popular, its users were
12

Rising Researchers

limited, and its applications had little impact on people’s lives. Today, however, utilization of informationand communication technology (ICT) has spreadthroughout society, and the Internet has become partof the infrastructure that supports our daily lives.
Systems outages affecting the Internet have thus
become unacceptable. Moreover, important information (such as credit-card numbers) is exchanged overthe Internet, so security breaches (such as the occurrence of financial damage) can occur if flaws in thesystem occur. People take it for granted that the Internet as a social infrastructure will always continue tooperate as expected without such problems, andexpectations concerning the reliability of the system
software that supports the Internet have risen enormously. A major problem, however, is that much of
the system software designed in the 1990s is still used
to support the current Internet—even though expectations concerning reliability have changed considerably.
The choice of programming language is critical inregard to a reliable system because the chosen language must prevent software defects and vulnerabilities that can lead to external attacks. As the current
mainstream programming language, C allows developers free and flexible manipulation of hardware,such as memory and central processing units (CPUs),
in a manner that makes it easy to maximize the performance of the hardware. However, programmingwith C, developed in the 1970s, is known to be risky
because it does not take safety into account; that is, C
is not contrived to assist developers in preventing
errors that cause bugs and vulnerabilities. In 2022,
the US National Security Agency issued guidelines
recommending the use of programming languages
other than C. Since around 2000, a number of safetyoriented programming languages targeting high-performance software have been proposed, and we are
currently working on one of them, Rust, with the aimof implementing new system software for supporting
the Internet.
—What are the characteristics of the Rust programming language?
The main feature of Rust is that it enables safe
implementation of high-performance software. For
example, the methods that the languages Java and Go
use for memory management prevent illegal memory
operations through a mechanism called “garbage collection,” which monitors memory usage while software is running and deallocates memory areas thatNTT Technical Review

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are no longer in use. Although garbage collection
assures safe memory operations, it has a negative
impact on performance because it operates duringexecution of software. In contrast, Rust does not use
garbage collection, which degrades performance;
instead, it is designed to infer memory usage when
the software is compiled (source-code conversion)and manage it appropriately. Although balancing
high performance and safety is a challenge, Rustachieves that balance by requiring developers to use
their own specific designs and expressions.
I’m currently working on implementing a Linuxbased operating system and a Border Gateway Protocol (BGP) daemon* (Fig. 1). As for the Linux operating system, we are working with developers fromother companies, such as Microsoft and Google, toimplement the core function (kernel) of the operating
system in Rust. Considering the software scale andpopularity of the Linux kernel, we believe that it is
not realistic to replace Linux with a new operating
system implemented in Rust; instead, we aim to
gradually replace the Linux kernel implemented in C
with one implemented in Rust.
Used in large-scale cloud infrastructure networks,
the BGP daemon, which supports the BGP (the backbone of the Internet), is a piece of system softwarethat requires high performance and reliability. Currently, BGP daemons implemented in C are widelyused; however, they lack the parallelism to takeadvantage of multiple CPUs, and they cannot exploit
the performance of modern hardware. We have therefore implemented a new BGP daemon that takes
advantage of Rust’s support for safely handling parallelism, and our BGP daemon has demonstrated fivetimes-higher performance than that of widely used
BGP daemons.
—What are some of the difficulties you are currently
facing in your research?
It takes time for new programming technologies tobecome widely used. In particular, the field of system
software, which forms the backbone of infrastructure,tends to take longer to adopt new technologies.
Many safety-focused programming languages havebeen developed to replace C; nevertheless, C is still thedominant language for system-software development.
One reason for C’s dominance may be the fact that it*

Daemon: A computer program that resides in the main memoryof a UNIX-like operating system such as Linux and provides
specific functions (such as background processes that perform
processing independent of user operations).

13

Rising Researchers

BGP (Border Gateway Protocol)

Internet
Edge server

Cloud service

Operating system

Fig. 1. Current targeted system software.

is a significant burden for developers to develop andmaintain software in a language other than C.
Additionally, in the case of Rust, its unique specifications not possessed by conventional languages are
said to be a barrier to its widespread use. In fact, it
was controversial when functions of the Linux kernel
were made available for implementation in Rust in
addition to C. After much discussion, it became possible to implement features of the Linux kernel in
Rust; however, at present, the Linux kernel does not
yet have any features implemented in Rust.
I realize that there is no shortcut to overcoming thiscurrent situation, so I’m being careful to first implement small functions in Rust and demonstrate theirusefulness. Specifically, when we proposed a featurethat would make it possible to implement device drivers that control network-communication hardware of
the Linux kernel in Rust, we encountered significant
resistance from developers. Acknowledging that
resistance, we are negotiating with such developers to
reduce the scope of the impact of Rust and allow
some features of network device drivers to be implemented in Rust.
In the field of development of open-source software (OSS), it is rare for 100% of your proposal to be
accepted, and in my younger days, I myself wasshocked every time my proposal was rejected. However, over the years of working in OSS development,
I have realized the importance of continuing to
improve and advance proposals with input from otherdevelopers and persisting even if only 10% of myproposals are accepted.
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Engage in research that involves many people
and has a big impact on the world—Please tell us about your future research vision.
As a next step, I believe we need to demonstrate thevalue of applying a safety-focused programming language such as Rust to system software. Since theLinux-kernel development community has been
divided on both sides of the Rust-application issue,
the question of whether it is sufficiently meritorious
to use a language other than C in development ofsystem software has not yet been answered. To
increase the usage of Rust for the Linux kernel, I
think it is necessary to get the widely used features
implemented in Rust adopted and demonstrate theirbenefits in terms of bugs and vulnerabilities. Moreover, since the use of a safety-focused programming
language like Rust cannot prevent all bugs and vulnerabilities, we plan to consider other approaches, forexample, preventing design defects.
By disseminating the results of our research on
preventing system-software bugs and vulnerabilities
as de facto technology, we aim to increase the reliability of system software throughout the industry. I
believe that this approach will not only improve thereliability of the infrastructure that supports our daily
lives but also enhance the value of our services by
allowing us to use resources previously spent on
addressing bugs and vulnerabilities to develop new
functions.
And in regard to the concept called the Innovative
14

Rising Researchers

Influencers

Early
adopters

Value creation
through opentype
development

NTT Group

Research
institues

Fig. 2. Vision of value creation through open-type development.

Optical and Wireless Network (IOWN) proposed byNTT, technologies for preventing system outages andunauthorized use are extremely important. In a worldin which life is more digitally integrated than everbefore through the IOWN and ICT becomes indispensable, frustration of users will grow more thanever if a “service has been suspended” situation
occurs. Aiming to avoid such situations and create asafe and comfortable society, we will continue to create an ecosystem involving various people besides
NTT by utilizing open-development methods such as
OSS to create new value on a global scale (Fig. 2).

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—Finally, please give a message to researchers, students, and business partners.
My research motto is “create technology that can beused by many people to further improve people’s
lives.” I still remember that shortly after I joined
NTT, my boss talked to me about my research topic,
and he asked me, “How many people could live off
the profits if the research results were to be commercialized.” I believe that his advice was not to aim fora technology that could only support the lives of a
few-dozen people and be used only within the group;
instead, it was to think of a theme that would make abigger difference in the world and affect tens of thousands of people. To this day, I still hold that advice inhigh regard. And technology itself only grows whensomeone uses it. I believe that having many people
use a technology will create a new market, and many
people will be able to make money from that technology; conversely, a technology that does not generatemoney will not spread.
My goal is to create technologies that will create
new markets for future research as well. My group is
conducting research not to keep such technologies
only at NTT but to spread them globally by using
open-development methods such as OSS in cooperation with other companies and to expand NTT’s
15

Rising Researchers

efforts by developing them into technologies withgreater impact. Although NTT takes a leading position when NTT and other companies collaborate inJapan, it is not a major player in major global OSS
projects. And since our interests are almost nevercompletely aligned with those of other companies,
we must adjust our interests and steer the project inthe direction we want it to go. Therefore, each time
we join a new community, we take the opportunity tomeet and talk with community members in person.
Although this activity seems simple enough, eveninformation that cannot be conveyed to other parties
through e-mail or online chat alone can be conveyed
through real face-to-face conversations with them. In
that way, we can increase the power and influence ofour voice within the community while deepening
understanding of other parties.
The Internet was originally created by many people, and to have an impact on the world, I myself will
not think alone in a laboratory; instead, I want to cre-NTT Technical Review

Vol. 21 No. 12 Dec. 2023

ate new value by getting involved with many people
and collaborating with them. I hope that you will join
me in activities that will have an impact on society.

Interviewee profile
Tomonori Fujita completed a master’s course at
Waseda University Graduate School of Scienceand Engineering in 2000. In the same year, hejoined Nippon Telegraph and Telephone
Corporation (NTT). He has been a distinguishedresearcher since 2015. He has been engaged in
R&D of system software (such as operating systems). He received the NTT President’s Award in
October 2014 and the Information Processing
Society of Japan’s Software Japan Award in
February 2015.

16

Feature Articles: Toward More Robust Networks

Operation to Achieve Robust
NetworksJun Okamoto, Tomoko Shibata, Mitsuho Tahara,
Masakatsu Fujiwara, and Masataka Masuda
Abstract

Large-scale communication-infrastructure failures have a tremendous impact on daily life and economic activities, requiring more resilient networks. We at NTT laboratories aim to achieve robust networks that minimize service impact by improving network adaptability to system failures and shorten
recovery time by improving network resilience. This article describes our research and development
efforts in operation-related technologies to achieve robust networks.
Keywords: robust network, operation, NW-AI

1. Toward robust networks
Network operations are becoming increasingly
complex due to virtualization technologies, complex
network configurations with commercial products,
and the vast amount of data distribution caused by thediversification of services. Information and communication technology (ICT) has been widely used invarious areas of social and economic life, and largescale communication-infrastructure failures will havea tremendous impact on people’s daily lives. Therefore, more resilient networks are required. We at NTT
laboratories have been conducting research anddevelopment (R&D) to achieve robust networks thatare highly resilient to network-system failures andlarge-scale disasters. This article introduces our R&D
efforts focusing on operation technologies to enhance
network-system fault tolerance.
2. Countermeasures against
communication-infrastructure failures
There are various causes of communication-infrastructure failures, such as chain failures due to software failures, abnormal traffic, operational errors,
and system anomalies. As network systems become
more complex, diverse, and virtualized, and as theuse of vendor-specific products leads to black boxes
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inside the systems, it is expected that countermeasures based on an understanding of equipment implementation and prior verification of assumed failure
events based on past cases will no longer be sufficient
to cover all types of failures. Therefore, to achieve arobust network, we discuss operation-related technologies from the viewpoints of foolproof, fail-safe,and fail-soft as a basic policy for communicationinfrastructure failure countermeasures based on theassumption that unexpected events are bound tooccur (Fig. 1).
•	Foolproof: Mechanisms to prevent human error
and effectively support human operations are
required. For example, functions to visualize
network failures and support recovery countermeasures by operators are considered.
•	Fail-safe: Mechanisms to prevent communication-infrastructure failures before they occur are
required, e.g., considering functions to prevent
failures of the communication infrastructure bycontrolling the frequency of failures throughredundancy of communication systems andexpansion of system resources and by regulating
the inflow of high-capacity traffic that causes
failures.
•	Fail-soft: Mechanisms to minimize the service
impact of communication-infrastructure failures
are required, e.g., considering functions that can
17

Feature Articles

Foolproof

Fail-safe

Fail-soft(Prevention of human error/operational support)(Prevention of failures)(Minimizing the impact of failures)(data, results, etc.)

Duplication

Service
Logical network(IP)
Logical network(Transmission)

Physical network

All ICT
resource
information
periodImproved restoration methods
Guidance on optimal recovery procedures
Response training for specific failures

Quality

Nationwide centralized systemfacility expansion
Increase

Transmission
equipment
Transmission
equipment

Resource extension
80%
Expansion

Area Aequipment

Area Bequipment

Area Cequipment

Service divisionHigh volume calls
Detect and destroy

NTT equipment

B

A

Area division installation

40%

Restrictions on inflow oflarge amounts of traffic

SenderDivision of nationwide
centralized system(Example) Resource utilization

Network
deviceVisualization and automation of
network-failure conditions
Visualization

Network
dvice

Development, design,and operation

How to develop and verify networks to ensure reliability

Mass transmission

Generalvoice

IoT

Quality management and assurance functions to confirm correct design and operation

IoT: Internet of Things

Fig. 1. Basic policy for countermeasures against communication-infrastructure failures.

Foolproof

Fail-safe

Fail-soft(Prevention of human error/operational support)(Prevention of failures)(Minimizing the impact of failures)

Development, design,and operation

How to develop and verify networks to ensure reliability
Visualization and automation of
network-failure conditions
Visualization(1) Visualization ofsituation(data,, results,, etc.)

Service
Logical network(IP)
Logical network(Transmission)

All ICT
resource
information

Nationwide centralized systemfacility expansion(2) Multiplexingof high-availability
Resource extension
Area division installation
control

Duplication
plication

Increase

TransmissionTranransm ss on(Example) Resource utilization

Expansion

Area Aequipment

Area Bequipment

Area Cequipment

40%

Physicaly
network

Improved restoration methods

amounts of traffic(3) Advanced coordinationlarge
between
Guidance on optimal recovery procedures
Response training
for specific failures and operation
verification

High volume calls
Detect and destroy

NTT equipment
SenderQuality

Division of nationwide
centralized system

A

B

Mass
M
ass transm
transmission
r
ransm
ss o
on

Service division
Generalvoice

IoT

Quality management and assurance functions to confirm correct design and operation

Fig. 2. Directions for strengthening resilience to communication-infrastructure failures.

divide an area or service so that a single device
failure does not spread to other services or otherareas.
To ensure the reliability of network systems, it isnecessary to consider countermeasures in each work
phase of development, design, and operation on thebasis of the above three viewpoints. Network quality
control and assurance functions should also be considered to monitor the correctness of the considered
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Vol. 21 No. 12 Dec. 2023

countermeasures in designs and operations.
To enhance network-system-failure resilience, wewill research and develop new technologies in thefollowing three directions to minimize unexpected
events in response to the increasing complexity,
diversity, and virtualization of network systems,
which are making network operations more difficult(Fig. 2).
(1) Visualization of situation18

Feature Articles

To take early countermeasures when a communication-infrastructure failure occurs, it is important tounderstand the network status and be able to identify
the failure location and factors. Therefore, we aim todevelop technologies that intelligently visualize thestatus of the network by using various types of information that can be obtained both inside and outside
the network, in addition to logs, alarms, and otherinformation output from the network devices that are
dependent on the device implementation.
(2) Multiplexing of high-availability control
To maintain system availability and reduce the riskof failures, it is important to have a variety of remedial measures for network systems. We aim to prevent communication-infrastructure failures and minimize service impact by implementing high-availability control technologies that provide multifaceted
remedial measures without limiting the system orservice.
(3)	Advanced coordination between verificationand operation
When service operations encounter unexpected
events, it is difficult to deal with them at earlier
stages, so it is important to minimize such events inadvance during system verification. Network systems
are becoming more complex with the use of virtualization technology and vendor-specific products, andservices are also becoming more diverse. Therefore,various events are affecting each other in complex
ways at a level far beyond human knowledge, resulting in the occurrence of unexpected events. Systemverification based on experience makes it difficult to
reduce unexpected events. Therefore, we adopt an
approach that drastically changes the traditional
experience-based verification method by using a
digital-twin environment of devices and networks.
With this verification method, the artificial intelligence (AI) extracts all verification conditions, generates simulated failures in a digital-twin environmenton the basis of the extracted conditions, and the otherAIs autonomously learn recovery countermeasures.
These AIs are then applied to actual operations in atimely manner to achieve advanced coordination
between verification and operation.
The new technologies to be created in these directions will improve the adaptability to network-system
failures, minimize service impact, and improve resiliency to achieve robust networks with shorter recovery times. In network operations, which are becoming increasingly difficult due to the growing complexity of network systems and the vast amount of
NTT Technical Review

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data being distributed, we aim to achieve automatedand autonomous operations in the future by proactively using AI.
3. Visualization of situation
As network systems become increasingly complex
and black boxed due to virtualization technology,
early detection of anomalies is important. Preventing
human error and providing effective support are also
important from the perspective of foolproof operation. We aim to solve these problems using AI andachieve self-evolving zero-touch operations that willautomate and autonomously operate networks in the
future.
An AI used in network operations is called an
NW-AI, and the flow of self-evolving zero-touch
operations using an NW-AI is shown in Fig. 3. The
NW-AI first collects configuration and observation
information inside the network and various information outside the network, such as weather, social
media, and local events. It next analyzes the collected
information and determines the next action. On thebasis of the results of the decision, it then executes
actions on the network system. By automaticallyrepeating this closed loop and developing an NW-AI
that learns autonomously, we aim to achieve selfevolving zero-touch operations.
The process of analysis and decision making by an
NW-AI enables visualization of network and service
conditions. When failures occur, the NW-AI firstdetects anomalies and their predictive signs by making more multifaceted judgments on the basis ofalarms from the system, traffic fluctuations, andinformation from peripheral devices and outside the
network. It next identifies the event and the range ofservice impact caused by the failures. It then estimates the failure locations and identifies the causes offailures. Traditionally, visualization of these conditions has been manually analyzed by operators usinglarge numbers of alarms output at each layer, such as
the physical network layer, logical network layer, andservice layer. However, this has taken a long time togain complete visibility of the situation. Development of an NW-AI that supports and automates thesetasks is expected to enable early detection of failures.
We are currently developing several NW-AI technologies, i.e., DeAnoSTM (Deep Anomaly Surveillance) [1], which models the normal state of systems
from various data using deep learning and detects
anomalies on the basis of deviations from the normal
state; alarm clustering, which aggregates alarms from19

Feature Articles

Analysis and judgment
NW-AI

Sense (e.g.. sensor)
sensorr)

Event identification
Ev

Impact identification

Cause determinationteermmination

Measure taking
MeasureMta(investigatio
tio(investigation)

Anormaly
Ano
orma
ma
aly
detection
dete
ec
e
cti
AbnormalAbn
bn
predictions
p

Incidentclustering

Service-impact
understanding

Failure-spot
estimation

Optimization
mizationrecommendation
me datimendatimen
dationonExternal
information

NW-AI
Observation
information

AIOps support

Configuration
information

Workflow engine

Information baseCollection

NMS
N
/EMS

Tool (esp.
software,
etc.)

NMS
/EMS

Tool (esp.
software,etc.)

Prediction
P
PredicPrer icctiotionnLogical network

Pseudo-fault
do-fa
do
fault
fa
ult
Simulation environment
Weather(meteorology) Map/traffic information
information

Provision of
information

MeasureControllerr llerrrolleroChangeover/exchange

Physical network

Terminal

Infrastructure(electricity, water, etc.)
information
EMS: element management system
NMS: network management system

Fig. 3. Self-evolving zero-touch operation flow.

systems into event units; NOIM (Network Operation
Injected Model) [2], which visualizes the serviceimpact range of failures; and DeAnoS-RCA (Deep
Anomaly Surveillance-Root Cause Analysis) andKonan (Knowledge-based autonomous failure-event
analysis technology), which estimate failure locations, etc. These technologies are introduced in thearticle “Technologies for Promptly Understanding
Network Conditions When Large-scale System Failure Occurs” [3] in this issue.
4. Multiplexing of high-availability control
To improve service availability in the event ofcommunication-infrastructure failures, current network systems have taken measures such as equipment redundancy and high-volume traffic-flow control. However, early failure recovery may be difficult
even with current countermeasures. Therefore, theissue is to ensure numerous remedies on the basis of
the assumption that unexpected events will occur.
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Vol. 21 No. 12 Dec. 2023

Although the implementation of multiple remedies
can improve the reliability of the system, it is expensive, making it difficult to evaluate the balance
between reliability and economic efficiency.
The mechanism to being considered to minimize
the service impact in the event of failures is fail-soft.
For example, devices can be divided and strengthened in areas or by service providers to prevent asingle-device failure from spreading to other areas orservices. As a fail-safe mechanism to prevent failuresfrom occurring and enable early recovery from failures, redundancy of devices and functions in network
systems is being considered. It is expected that network virtualization will make it possible to securesystem redundancy more economically in the future.
Resource multiplexing, layer multiplexing, network
service multiplexing, etc. are being considered as
redundancy mechanisms to increase high availabilityof services.
Regarding resource multiplexing, resources in a
virtualized and distributed system required for each20

Feature Articles(3) Model/data transfer
Analyze differences between environments
when learning models/applying NW-AI
Alarm
Log

(2) Verification and AI learning
using chaos engineering
Failure response
DB/NW-AI

Alarm
Log

NW-AI applied

Chaos
Model
learning

Alarm

Commercial service
delivery environment

Event
insertion

Alarm

Log

trafficdata
datatraffic
data
Traffic

Insert event
tools(1) Event generation• Traffic-data analysis• Event generation for verification
1. Verification events based on
steady-state values of real
traffic
2. Verification events based on
analysis of anomaly eventsin real traffic
3. Validation events based on
prediction of future changes
based on actual traffic trends

Log
Data-generation-environment
construction (network
configuration information,
alarms, logs, traffic data, etc.)

Digital-twin environment orverification environment

DB: database

Fig. 4. Framework for advanced coordination between verification and operation.

service and spare resources for redundancy are optimally allocated in advance from the hardwareresource pool. When an anomaly occurs and spareresources are insufficient, emergency resources forescaping from the anomaly spiral or resources
already allocated to other services are temporarily
allocated. Mechanisms for sharing and isolating
hardware resources are also being considered toreduce interference between services.
In layer multiplexing, the independence of each
network layer, such as transport networks, Ethernet
networks, and Internet Protocol (IP) networks, ismaintained under normal conditions, and optimal
control is executed by inter-layer collaboration when
failures occur. Redundant design and control are carried out in consideration of the dependencies amonglayers, and mechanisms to deter anomalous external
events at the optimal layer are being considered.
In network-service multiplexing, mechanisms toprevent the occurrence of total large-scale failuresthrough the multiplexing of various network services
are being considered. Examples include access network multiplexing, in which wireless access is
switched to other systems in the event of an anomaly,
and core network multiplexing, in which network
slices and optical paths are switched in considerationof the quality-of-service level in the event of ananomaly in a virtualized network. Specific technologies for network service multitasking, transmissionnetwork redundancy, etc. are introduced in the article
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“Network Reliability Design and Control Technology
for Robust Networks” [4] in this issue.
5. Advanced coordination between verificationand operation
When various services are provided, various verification tests are conducted in the development andconstruction of devices and systems. However, it isdifficult to cover all failures in network systems,
which are increasingly complex and black boxed due
to virtualization technology and other factors. Therefore, the challenge in network operations is to findways to handle events that exceed the assumptions ofdevice developers and system designers. Anotherchallenge is to create a network-operation frameworkthat eliminates human error and efficiently handles
unexpected events.
We are studying a framework for advanced coordination of verification and operation by using thedigital-twin environment and verification environment. This framework is shown in Fig. 4. First, anenvironment simulating network systems with commercial services is constructed on a digital twin orverification environment. In the simulated environment, variations of failure events are artificially generated using chaos-engineering tools that generate
pseudo-failures. Therefore, the possibility of extracting unexpected events is increased. The goal is todevelop an NW-AI that can autonomously recover21

Feature Articles

from failure events. The key points of technicaldevelopment are as follows.
(1) Event generation
Verification conditions, such as failure events, aregenerated artificially by using an NW-AI. Theseverification conditions are efficiently generated on
the basis of the analysis results of traffic-data flows incommercial services.
(2)	Verification and AI learning using chaos engineering
Failure events based on the generated verification
conditions are generated in a simulated environment
using a chaos-engineering tool. Thus, the system’s
behavior under conditions that are out of the scope ofthe equipment developer’s or system designer’s
assumptions can be understood. By autonomously
learning system behavior and countermeasures in thesimulated environment, an NW-AI can cope with
unexpected events in a commercial-service environment. The learning of system behavior and countermeasures in the simulated environment is not limited
to training of the NW-AI but also intended to be used
for training network operators.
(3) Model and data transfer
The simulated environment is assumed to be averification environment for service development ora digital-twin environment built with digital technology. The higher the similarity, the more similar theverification to commercial services. However, since
it is difficult to perfectly match the commercial andverification environments, transfer technologies are
required to apply the NW-AI models and data learnedin the simulated environment to the commercial environment.

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Details of this framework are introduced in thearticle “NW-AI Self-evolving Framework for Faulttolerant Robust Networks” [5] in this issue.
6. Future developments
This article introduced R&D efforts in operationrelated technologies for robust networks. We aim toachieve more resilient networks against communication-infrastructure failures and disasters and theoperations that support them by implementing thetechnologies in the R&D stages described in thisarticle. We will also accelerate R&D on an NW-AI toachieve self-evolving zero-touch operations that willautomate and autonomously operate networks in the
future.
References
[1]

[2]

[3]

[4]

[5]

K. Watanabe, K. Tajiri, and Y. Nakano, “Deep Learning Based
Anomaly Detection Technology for ICT Services—DeAnoS: Deep
Anomaly Surveillance,” NTT Technical Review, Vol. 17, No. 7, pp.
17–20, July 2019. https://doi.org/10.53829/ntr201907fa3
M. Sato, S. Nishikawa, K. Murase, and K. Tayama, “Technology for
Understanding Service Impact Using Network Resource Management
Technology that Is Independent of Network Type,” NTT Technical
Review, Vol. 18, No. 11, pp. 48–52, Nov. 2020. https://doi.
org/10.53829/ntr202011ra2
K. Akashi and S. Kanai, “Technologies for Promptly Understanding
Network Conditions When Large-scale System Failure Occurs,” NTT
Technical Review, Vol. 21, No. 12, pp. 24–26, Dec. 2023. https://
ntt-review.jp/archive/ntttechnical.php?contents=ntr202312fa2.html
T. Matsukawa, K. Koshiji, and T. Tojo, “Network Reliability Design
and Control Technology for Robust Networks,” NTT Technical
Review, Vol. 21, No. 12, pp. 27–32, Dec. 2023. https://ntt-review.jp/
archive/ntttechnical.php?contents=ntr202312fa3.html
Y. Takahashi, H. Ikeuchi, and A. Watanabe, “NW-AI Self-evolving
Framework for Fault-tolerant Robust Networks,” NTT Technical
Review, Vol. 21, No. 12, pp. 33–36, Dec. 2023. https://ntt-review.jp/
archive/ntttechnical.php?contents=ntr202312fa4.html

22Feature Articles

Jun Okamoto

Project Manager, Executive Research Engineer, Supervisor, Communication Traffic, Quality and Operation Research Project, NTT Network Service Systems Laboratories.
He received a B.E. and M.E. in electrical engineering from Tokyo University of Science in1994 and 1996. He joined NTT in 1996 and has
been engaged in the quality assessment of telecommunication and network performance measurement methods. Currently, he is manager of
the Communication Traffic, Quality, Operation
Research Project in NTT Network Service Systems Laboratories. He received the Telecommunications Advancement Foundation Award in2009 and the International Telecommunication
Union Encouragement Award in Japan in 2010.
He is a member of the Institute of Electronics,
Information and Communication Engineers(IEICE) of Japan.

Tomoko Shibata

Project Manager, Executive Research Engineer, Supervisor, Access Network Operation
Project, NTT Access Network Service Systems
Laboratories.
She received a B.S. in chemistry from Hokkaido University in 1995 and joined NTT thesame year. She is now in charge of R&D management strategies of access network operation. She
is a member of IEICE.

Masakatsu Fujiwara

Director, Planning Department, NTT Information Network Laboratory Group.
He received a B.E. in electrical engineeringand M.E. in applied systems science from Kyoto
University in 1994 and 1996, and an M.B.A.
from Cornell University, USA, in 2005. After
joining NTT Network Service Systems Laboratories in 1996, he was engaged in the R&D of key
technologies for network-management systems
from 1996 to 2007 and 2010 to 2013. He was
director of NTT R&D European Representative
Office in Frankfurt, Germany, from 2013 to2017.

Masataka Masuda

Group Manager, Senior Research Engineer,
Supervisor, Traffic Engineering Research Group,
Communication Traffic, Quality and Operation
Research Project, NTT Network Service Systems Laboratories.
He received a Ph.D. in engineering from theTokyo University of Agriculture and Technology
in 2011. Since joining NTT in 1999, he has been
engaged in the R&D of communication quality,
multimedia service quality evaluation, and network-operation technologies. He received theYoung Investigators’ Award from IEICE in 2002
and the Technical Committee on Communication
Quality’s Award from IEICE in 2004. He is amember of IEICE.

Mitsuho Tahara

Project Manager, Executive Manager, Network
Operation Project, NTT Network Innovation
Center.
He received a B.E. and M.E. in electronicengineering from the University of Tokyo in
1995 and 1997. Since joining NTT Network
Service Systems Laboratories in 1997, he has
been engaged in the R&D of operation-support
systems. He is a member of IEICE.

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

23

Feature Articles: Toward More Robust Networks

Technologies for Promptly
Understanding Network Conditions
When Large-scale System Failure
OccursKazuaki Akashi and Shunsuke Kanai
Abstract

NTT laboratories are developing enhanced operational technologies to make communication networks robust. In this article, we introduce NTT research and development initiatives to promptly understand the network conditions and the impact of failures on complex network services when a large-scale
system failure occurs.
Keywords: communication network, fault management, large-scale failure

1. Introduction
NTT laboratories are researching and developing
operational technologies to make communication
networks robust. In this article, we introduce the Network Operation Injected Model (NOIM), which centrally manages networks composed of various communication protocols and enables early detection of
the impact of failures on network services, DeAnoSTM(Deep Anomaly Surveillance), which detects anomalies, and Konan (Knowledge-based Autonomous
Failure-Event Analysis Technology for Networks),
which detects the cause of failures by using prelearned rules.
2. Network-resource-management technology
Network services are provided by multilayer networks that combine different communication protocols, such as optical-transmission networks, Ethernet
networks, and Internet protocol (IP) networks.
Because these networks are typically managed byseparate systems, the effects of a network failure at
one layer on networks and services at other layers
must be manually analyzed. However, when a largeNTT Technical Review

Vol. 21 No. 12 Dec. 2023

scale failure occurs, it takes a long time to understandthe network status and service impact because thelocation of the failure and its impact are widespread.
We developed the NOIM to enable early understanding of service impact [1]. The NOIM enables thecentral management of complex multilayer networks
and quick understanding of the impact of failures onservices by expressing network information in a common data model that does not depend on layers suchas termination points and forwarding relationships.
The NOIM uses a common data model that is basedon the Shared Information/Data Model (SID) discussed in the TM Forum [2] to achieve networkresource management. It uses the entities defined as
the Physical Resource and Logical Resource in the
SID. The SID Physical Resource defines entities, i.e.,
PhysicalDevice, PhysicalLink, PhysicalStructure,
and AggregationStructure, that represent physicalresources, i.e., routers, cables, buildings, and pipelines, respectively. Similarly, the SID Logical
Resource defines entities, i.e., TerminationPointEncapsulation, the NetworkForwardingDomain, andForwardingRelationshipEncapsulation, that represent the logical resources of a network, i.e., termination points, relationships, and domain in each layer,
24

Feature Articles

Logicalresource

IP layer
ForwardingRelationshipEncapsulation
Ethernetlayer
TerminationPointEncapsulation
Optical-transport
layer

NetworkForwardingDomain

Logical-devicelayer

Physicalresource

Cable

Building
Physical layerIProuterPhysicalStructure

Layer 2switchTransport
devicePhysicalDevice

PhysicalLink

FailureTransport
deviceLayer 2switchIProuterAggregationStructure

Fig. 1. Multilayer network-resource management with common data model.

respectively. By using these entities to represent eachresource and the connection relationship between
resources, as shown in Fig. 1, the NOIM makes it
possible to manage multilayer networks composed ofvarious communication protocols.
The NOIM also provides a mechanism for externally defining characteristics specific to each communication protocol and managing them by linking
them to the above generic entities. Example characteristics are IP addresses in IP networks and VLAN
IDs (virtual local area network identifiers) in Ethernet networks. Common characteristics that do notdepend on the communication protocol are represented by entities, and unique characteristics can be
added as external definitions, allowing flexibility
when adding or changing communication protocols
and services.
The NOIM quickly determines service impact
when a failure occurs. For example, when a pipeline
is cut, as shown in Fig. 1, due to a natural disaster, thecables contained in the pipeline and the logicalresources of each layer on the cables are affected by
the failure. The NOIM can easily determine which
physical and logical resources are affected by a failure by tracing relationships between resources thatare represented with common entities such as AggregationStructure, PhysicalLink, TerminationPointEncapsulation, and ForwardingRelationshipEncapsulation. There is no need to change the trace logic even
if the network layer configuration changes.
Unlike cable disconnections or building blackouts
caused by natural disasters, a network system failure
NTT Technical Review

Vol. 21 No. 12 Dec. 2023

causes parts of the network and service to become
unstable. To accurately determine the area affected bya system failure and the number of users in such an
event, it is necessary to determine service impact byconsidering traffic flows for each service and unstable paths in the network. Therefore, as shown in
Fig. 2, we are working on the following enhancements to the NOIM to support large-scale failure
response.
(1) Adding a service-path layer
To provide a more granular view of service impact,
we add a service-path layer to the common data
model in the NOIM. This layer of logical resources
represents the end-to-end connectivity of the services
provided on the network. Service impact is currently
determined at the same granularity as communication
protocols, but the addition of a service-path layer
makes it possible to determine service impact at any
granularity, such as per area or per user.
(2)	Understanding service impact by considering
traffic flows
We enable the NOIM to identify unstable services
due to network system failures on the basis of whether the traffic for each service is flowing through an
unstable communication path. Therefore, we represent the traffic flow of each service as a combinationof resources and determine the status of the service on
the basis of the status of those resources.
(3) Understanding unstable communication paths
We identify unstable communication paths due tocongestion by comparing the bandwidth required for25

Feature Articles

Network

Unstable services
FailureInternet

Service-pathlayer

IP layer

Service B

Congestion

IP characteristics(+ bandwidth)

Ethernetlayer

Ethernet
characteristics(+ bandwidth)

Optical-transportlayer

Optical-transportcharacteristics(+ bandwidth)

Physical layer

Service A

Service-pathcharacteristics(+ bandwidth)

Traffic flows• • • •

Fig. 2. Overview of network-resource-management technology for large-scale failures.

each service path with that of the resources traversedby the traffic flow. Because the factors that cause
network instability are not limited to out of bandwidth, it is necessary to understand the unstable paths
by using not only the NOIM but also anomaly-detection and failure-cause-estimation technologies.
3. Anomaly-detection andfailure-cause-estimation technologies
To early detect network faults and rapidly identify
the cause of failure, we are also researching anddeveloping the following artificial intelligence technologies for detecting anomalies and estimating failure resources from network information such as
alarms.
•	DeAnoSTM: This technology enables a proactive
control network that can detect potential performance-degradation risks (failures, congestion,etc.) and demand changes in a predictable andearly manner and execute proactive control andearly and automatic recovery.
•	Konan: This is a technology for estimating thecause of failure in a multilayer network. It learns
Kazuaki Akashi

Senior Research Engineer, Access Operation
Project, NTT Access Network Service Systems
Laboratories.
He received a B.S. and M.S. from The University of Electro-Communications, Tokyo, in 2009
and 2011. He then joined NTT in 2011 and has
been engaged in the research and development ofaccess network operations and in the development, maintenance, and management of internal
IT systems.

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

the occurrence status of alarms when a failure
occurs on the network as a rule. On the basis of
the learned rules and alarm information at thetime of the failure, it can efficiently estimate
resources that caused the failure, not only thephysical resource but also logical resources.
4. Conclusion
We explained operational technologies to achieve arobust network. NTT laboratories will promote not
only the development of individual technologies but
also a zero-touch operation framework for the cooperation and introduction of these technologies, contributing to the early understanding of network conditions and the speedup of recovery responses.
References
[1]

[2]

M. Sato, S. Nishikawa, K. Murase, and K. Tayama, “Technology for
Understanding Service Impact Using Network Resource Management
Technology that Is Independent of Network Type,” NTT Technical
Review, Vol. 18, No. 11, pp. 48–52, Nov. 2020. https://doi.
org/10.53829/ntr202011ra2
TM Forum, https://www.tmforum.org/

Shunsuke Kanai

Senior Research Engineer, Access Operation
Project, NTT Access Network Service Systems
Laboratories.
He received a B.S. in mathematics from Tokyo
University of Science in 1998. He obtained an
MBA in 2004 and Ph.D. in social engineering in
2016. He joined NTT in 1998, where he worked
in facility investment planning for access networks and has been engaged in the research anddevelopment of network operations and network
device management and control.

26

Feature Articles: Toward More Robust Networks

Network Reliability Design andControl Technology for Robust
Networks
Tatsuya Matsukawa, Kohjun Koshiji, and Takuya Tojo
Abstract

NTT Network Service Systems Laboratories is engaged in research on network design and control
technologies for further strengthening networks against large-scale disasters and failures. As a countermeasure against large-scale disasters, we are conducting research and development to enhance the disaster and fault tolerance of transmission routes. As a countermeasure against large-scale failures, we areinvestigating robust control-plane architectures that can prevent prolonged and large-scale failures. We
are also investigating technologies for improving user-level connectivity by linking information-accessdevices and the cloud. Three of these technologies are introduced in this article.
Keywords: redundant design, signal control, multipath control

1. End-to-end reliability design
To provide stable network services to customers at
all times, it is necessary to improve the reliability of
the network from end-to-end. It is necessary to maintain and improve end-to-end reliability, which covers
access, transport, and core networks as well as devices and cloud services (Fig. 1). NTT Network Service
Systems Laboratories (NS Labs) has been researching technologies for evaluating network reliability
during the design phase and for supporting network
operation after launch of services. In some cases,
telecommunication services have been unavailable
for long periods due to the occurrence of large-scaledisasters or network failures that have affected theuse of services by a large number of customers. As acountermeasure against large-scale disasters,
advanced design techniques are key factors in reducing the impact of such disasters by making networks
redundant. As a countermeasure against large-scale
failures, it is necessary to implement mechanisms,
such as control functions, in the network to avoid
events such as congestion. It is important to maintainand improve end-to-end reliability, including that ofaccess networks, transmission networks, core netNTT Technical Review

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works, and even terminals and cloud services. Network design and control not only protects network
services from disasters and failures but also provides
flexibility needed to increase network service levels
by securing resources in cooperation with functions
and systems outside the network. As network designand control technologies to improve end-to-end reliability, designing network redundancy, strengthening
the control plane, and assuring end-to-end communication robustness are introduced in this article.
2. High network reliability through redundantroute design
As networks continue to increase in speed, capacity, and latency, the requirements concerning reliability are becoming increasingly stringent. In particular,a transport network, which is the foundation of thewhole network, accommodates a large number ofusers and services, so interruptions to services caused
by failures can have a devastating impact. It is therefore important to ensure high reliability by implementing a combination of reliability measures suchas equipment redundancy and decentralized arrangement [1]. Since transport networks can be damaged
27

Feature Articles

Cloud

Core
network

End-to-end(Independently
ensure reliability
in each section)

User
plane

Isolation
Control plane

Transport
network

Access networkand terminals

Fig. 1. End-to-end reliability.

End point 1

Backup system(1st candidate route)Transport network

In-usesystem(shortest route)(3) Shared useof pipelines(1) Selection of
backup route

Central officeFiber

Backup system(2nd candidate route)End point 2(2) Designationof transit buildings(4) Expansion of
expected disaster area

Fig. 2. Redundant route design in transport network.

by external factors, such as disasters and failures, it isimportant to identify risk factors in advance anddesign physical routes that avoid those risks. It is also
important to set up a backup route and—in case of
emergency—use it as an alternative that maintains
communications. While network redundancy usually
minimizes the impact on services in the event of a
failure, the disaster resilience of transmission routes
depends on their length, shape, and geographic
arrangement. In addition to the disaster resilience ofeach of the in-use and backup routes, it is importantthat either of the routes functions normally in theevent of a disaster. To address these issues, NS LabsNTT Technical Review

Vol. 21 No. 12 Dec. 2023

considered the following two requirements.
The first requirement is that the in-use and backup
routes must be highly fault-tolerant and disasterresistant. For instance, a shorter route is less susceptible to disasters, and the probability of encountering
a malfunction is lower when the route passes throughfewer devices (Fig. 2(1)). In this case, it is importantto reduce the distance and number of devices along
the route. By preferentially selecting facilities constructed for disaster countermeasures, it is possible todesign a highly disaster-resistant route (Fig. 2(2)). In
this case, it is necessary to devise a procedure forselecting a route between the design target locations
28

Feature Articles

Number of in-use-route/backuproute candidates

Table 1. Comparison between our and conventional algorithms.
Total number of designated transit points
1

2

3

4

5
10

5

Since the set number of candidates
is small, the conventional algorithm
cannot obtain an appropriate routeas a solution. ( )Conventional algorithm may notprovide an appropriate route as asolution. ( )

20
30
50

Appropriate routes were obtainedeven with conventionalalgorithm. ( )100

Due to the increase in the amount ofcalculation, with the conventionalalgorithm, memory errors occur, andprocessing is not completed. ( )by specifying network facilities (such as central
offices and links) to be routed or not routed.
The second requirement is that the backup route
must function properly in the event of a disaster or
failure on the in-use route. For example, if two fiberroutes are housed in the same pipeline, there is a riskof damage to both fibers in the event of a failure of
the pipeline (Fig. 2(3)). A single failure can affectboth routes, thereby posing a risk of interruption toservices. As more network equipment is shared, therisk of service interruption becomes greater, and network redundancy becomes lower. The concept of ashared-risk link group (SRLG) is known as a state inwhich multiple network facilities share the same risk,
and it is important to select routes in consideration of
the risk of simultaneous failures of the in-use andbackup routes. Even if the in-use route and the backup route are separate by some distance, if the expected area affected by a disaster (such as an earthquakeor flooding) straddles both routes, both routes may bedamaged in the event of a disaster (Fig. 2(4)). By
defining a disaster or failure that affects multiple
equipment and facilities simultaneously as a sharedrisk and assigning the same risk-group identifier (ID)to the facilities that share the risk, we have made it
possible to search for routes that avoid the shared
risk.
Many algorithms, such as Dijkstra’s algorithm, forfinding the shortest route in a network are available.
However, a route-search algorithm that satisfies thetwo above-mentioned requirements has not been considered. NS Labs therefore developed an algorithm
for finding routes that satisfy the two requirements,
and we verified it through simulation. To satisfy the
first requirement, we developed a method thatNTT Technical Review

Vol. 21 No. 12 Dec. 2023

involves using the k-SPF (shortest-path first) algorithm, which is a heuristic-solution method that finds
the number of routes (k) between specified destinations in order of ascending cost (length of route) [2].
To satisfy the second requirement, we then devised analgorithm for finding in-use and backup routes byassigning IDs to SRLGs such as pipelines and disaster-forecast areas and generating in-use and backup
routes without duplicating those IDs [3]. In a previous study [4], it was not assumed that the searchwould specify a transit point or generate multiple inuse and backup routes between start and end points.
We found that searching for a route that satisfies thetwo requirements by using the results of previous
research would require a large amount of memory forcomputation owing to the huge amount of computation required. We also found that a candidate routethat should be found by the search process may not befound if the amount of memory is insufficient. Therefore, applying our in-use-route/backup-route searchalgorithm, we divided the search sections into “startpoint to transit points,” “transit points to end point,”
and “end point to transit points” and searched forroutes from the start point to the transit points, fromthe transit points to the end point, and back to the startpoint in that order. This algorithm can reduce thesearch area by narrowing down the search targets sothat the same route is not selected during the routesearch process. Example results of comparing ouralgorithm and the conventional algorithm are shownin Table 1. The table shows the evaluation results forthe optimal route for the total number of candidate
routes and transit points specified for the in-use andbackup routs. From these results, with the conventional algorithm, the amount of spatial calculation
29

Feature Articles

Robust signal-control bus and shared data layer

Robust control mechanism

Shared data layer
Auto scaling

Messagemanagement/control

Load distribution

Service-update
management

Quantification/visua
lization/notification

Auto healing

NEF

NRF

Robustsignalcontrol
bus

Control according toservice/terminal

Systembehavior
analysisengineAI-driven analytics

N1
UE

AMF: access and mobility management function
AUSF: authentication server function
DN: data network
NEF: network exposure function
NRF: network repository function
NSSAAF: network slice-specific authentication and authorization function

AMF

SMF

N2

N4

RAN

UPF

N3

UDM

Deploying network
interfunction
proxies

AUSF

N6

PCF

NSSAAF

DN

PCF: policy control function
RAN: radio access network
SMF: service management function
UDM: unified data management
UE: user equipment
UPF: user plane function

Fig. 3. Robust signal-control architecture.

(i.e., amount of memory required for calculation)
increases exponentially with the number of facilities;
however, with our algorithm, it can be reduced topolynomial time, so it can be considered practical andeffective. Our algorithm can reduce memory usage,
so we expect it to be used in actual network-designphase.
3. Toughening of control plane bysignal-control bus
Several large-scale failures of telecommunications
on mobile communication networks have occurred inJapan. There are three cited common causes and characteristics of such large-scale failures: (i) high loadsuch as location-registration processing; (ii) failed
control functions causing network congestion thatspreads throughout the network; and (iii) problems
such as data inconsistency that degrade database processing and increases recovery time. Several papers
related to these issues have been published by theInstitute of Electronics, Information and Communication Engineers (IEICE) [5]. At the 3rd Generation
Partnership Project (3GPP) workshop held in June
2023 [6], the resilience of core networks was also
NTT Technical Review

Vol. 21 No. 12 Dec. 2023

raised concerning mobile communication networks,
and future measures will be discussed by telecommunication carriers and vendors from now on. NS
Labs has therefore been studying architectures aimed
at toughening the control plane [7]. We are investigating implementing a robust signal-control bus composed of a group of network-control functions tomanage and control the exchange of signals between
network functions (Fig. 3). The signal-control bus
has two characteristic features: (i) the control planeand user-data plane are separated and (ii) the control
plane is based on a service-based architecture, whichenables timely addition of functions in accordancewith application characteristics and the development
cycle of the application. We are also investigating afunction to recover from performance degradation byautomatically adding resources when user accesses
become concentrated or processing load increases.
Redundancy and automatic addition of resources tothe control bus that connects functions can also avoid
the effects of signal congestion and other problems.
At 3GPP, a service communication proxy has been
proposed as a function based on a similar concept. NS
Labs is investigating a signaling-control scheme
based on the type of service or terminal and the30

Feature Articles

Cloud/MEC
Cooperative
control gateway

Cooperative
multipath function

Cooperative infrastructure platform
Multipath communication method• Dynamic network switching• Aggregation• Redundant transmission

Mobile network

Mobile network

Terminal

Fig. 4. Multipath control technology for cooperative infrastructure platform.

signaling load in the signaling-control bus as an additional feature to make the response more flexible
when signaling congestion occurs. In the future,devices other than mobile communication devices
will be connected to the network. We believe that
controlling signals in accordance with the status ofterminals and devices will help mitigate the effects ofcongestion by maintaining high-priority communication connections or reducing the amount of signals in
the network in case of emergency.
To detect failures and anomalies in the network andquickly mitigate their effects, the above-mentioned
signal-control-bus architecture requires a mechanism
to visualize the causes of failures and anomalies andenable quick predictive detection. For a mechanism
for detecting service anomalies in the network, we areconsidering a function that uses probes to detect
anomalies in each functional part of the network andnotifies the signal-control mechanism when it detects
an anomaly. We believe that such detection and notification of anomalies within the network and controlof them in coordination with other functions will
enable quicker response to failures.
4. Robust end-to-end communication throughmultipath control technology
In addition to improving intra-network robustness,
NS Labs is also working on multipath communicaNTT Technical Review

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tion—which features increased end-to-end robustness—by using multiple networks between the terminal and the cloud/multi-access edge computing(MEC). Multipath communication is a form of communication that has multiple paths between terminals
and servers in a manner that increases the robustnessof the system. Using a combination of networks withdifferent characteristics, such as mobile networks ofdifferent carriers or private fifth-generation mobile
communication system (5G) and carrier 5G, makes it
possible to minimize the impact of communication
breakdowns due to a failure in one network, deterioration of radio-wave conditions, etc. by communicating via a normal network or a network with goodradio-wave conditions.
To improve the effect of robustness in multipath
communication, a control technology that uses multiple networks is needed. Therefore, we are developing a cooperative infrastructure platform [8] for mission-critical services and investigating a cooperative
multipath function as a multipath communication
technology that connects terminals to the cloud andMEC (Fig. 4). The cooperative multipath function
provides optimal multipath communication according to user and application requirements. Specifically, it provides three multipath communication methods: (1) dynamic network switching, which uses only
a specific network under normal conditions and switches networks in the event of failure; (2) aggregation,
31

Feature Articles

which uses multiple networks simultaneously bysorting packets on a per-packet basis; and (3) redundant transmission, which sends copies of packets tomultiple networks. These methods for improving
robustness are effective, but they differ in terms ofdelay, bandwidth, and reliability. With method (1),
network quality, such as delay and jitter, is expected
to be stable because the same network continues to be
used under normal conditions. Method (2) is expected to increase available bandwidth, although latency
and jitter may fluctuate due to the use of different
networks. Method (3) is less efficient in terms of
bandwidth utilization because the same packet is sent
multiple times; however, it is more tolerant of packet
loss and is expected to reduce latency because thereceiver can process packets that arrive first. The
cooperative multipath function works with the cooperative control gateway, which executes cooperative
control between the terminal and the cloud and MEC
and provides appropriate multipath communicationaccording to user and application requirements andnetwork-communication conditions.

Tatsuya Matsukawa

Senior Research Engineer, Optical Transport
Research Group, Core Network Technology
Research Project, NTT Network Service Systems Laboratories.
He received a B.E. and M.E. from Osaka University in 2000 and 2002. In 2002, he joined NTT
Service Integration Laboratories, where he wasengaged in research on network reliability for the
next generation network (NGN). He also worked
on network operation in NTT EAST. He is currently engaged in the research and developmentof robust network architecture and network
design for the All-Photonics Network. He is amember of IEICE.

Kohjun Koshiji

Senior Research Engineer, Optical Transport
Research Group, Core Network Technology
Research Project, NTT Network Service Systems Laboratories.
He received a B.E. and M.E. in management
science from Tokyo University of Science in2007 and 2009. He joined NTT in 2009 andworked on reliability evaluation, design, andmanagement of telecommunication networks.
He is currently involved in optical transport network design. He is a member of IEICE.

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

References
[1]
[2]

[3]

[4]

[5]
[6]
[7]
[8]

Website of NTT, “Improving Network Reliability,” https://group.ntt/en/disaster/3principles/nw.html
H. Matsuura, K. Koshiji, Y. Kaneko, H. Yokoi, T. Matsukawa, T. Fujii,
and T. Miyamura, “Redundant Routing on Optical Networks Using
k-SPF Algorithm,” IEICE Society Conference, B-12-2, 2022 (in Japanese).
H. Matsuura, K. Koshiji, Y. Kaneko, H. Yokoi, T. Matsukawa, T. Fujii,
and T. Miyamura, “Finding SRLG-disjoint Primary and Backup
Route Pairs Using k-SPF Algorithm in Optical Networks,” IEEE
Global Communications Conference 2023 (accepted).
Y. Yang, H. Mi, and X. Zhang, “A Minimum Cost Active and Backup
Path Algorithm with SRLG Constraints,” Proc. of the 6th International Conference on Internet Computing for Science and Engineering(ICICSE 2012), Zhengzhou, China, April 2012. https://doi.
org/10.1109/ICICSE.2012.29
Y. Kasuga and A. Nakao, “Control-Plane Slicing for Mitigating Congestion In mMTC for 5G Mobile Core,” IEICE Tech. Rep., Vol. 122,
No. 198, NS2022-93, pp. 76–81, 2022.
3GPP documents, https://www.3gpp.org/ftp/tsg_sa/TSG_SA/
Workshops/2023-06-13_Rel-19_WorkShop/Docs/
Website of NTT R&D, “R&D Activities for 6G/IOWN Network
Architecture: Inclusive Core,” https://www.rd.ntt/e/ns/inclusivecore.
html
T. Kuwahara, R. Ishibashi, K. Kawakami, H. Matsutani, H. Yamamoto, and S. Yasukawa, “Cooperative Infrastructure Platform for
Delivering Mission-critical Services,” NTT Technical Review, Vol.
19, No. 10, pp. 44–50, Oct. 2021. https://doi.org/10.53829/
ntr202110fa5

Takuya Tojo

Senior Research Engineer, Group Leader, Network Service Platform Research Group, Network Technology Research Project, NTT Network Service Systems Laboratories.
He received a B.E., M.E., and Ph.D. from
Tokyo Denki University in 2002, 2004, and2007. In 2004, he joined NTT Service Integration
Laboratories, where he was engaged in researchon network architecture, quality of service, andtransport protocols for the NGN. He also worked
on designing the IP backbone network at NTT
DOCOMO. Since 2015, he has been engaged in
IP and optical network architecture, multilayer
SDN control, and network slicing. He is currently engaged in research and development of a
network-service platform for mission criticalservices such as autonomous driving.

32

Feature Articles: Toward More Robust Networks

NW-AI Self-evolving Framework for
Fault-tolerant Robust Networks
Yousuke Takahashi, Hiroki Ikeuchi, and Akio Watanabe
Abstract

We at NTT laboratories are focusing on the research and development of zero-touch operations using
artificial intelligence (AI) for early recovery from network failures, which requires learning a large
amount of network failure data. We have established a framework that allows AI to learn autonomously
by artificially generating a large amount of network failures in a simulated environment and learning
how to respond to them. This article describes the concept of this framework and how AI learns in theframework.
Keywords: self-evolving AI, chaos engineering, digital twin

1. Introduction
NTT laboratories are aiming to develop robust networks that are resilient to unexpected failures. To
achieve this goal, we are researching and developing
how to automate network operations and ultimately
achieve zero-touch operations using artificial intelligence (AI). At the heart of these efforts is an AI for
network operations, which we call NW-AI.
In zero-touch operations, NW-AI operates andmanages the network with minimal human intervention. Specifically, it automatically performs tasks
such as anomaly detection and failure location estimation. For example, NW-AI can monitor network
communication patterns and performance data todetect network anomalies. When a failure occurs,
NW-AI can analyze network topology information
and a large amount of log data to estimate the causeof the failure.
One of the most challenging tasks is the automatedrecovery of network failures by NW-AI. Automatedrecovery of network failures is a key element in maintaining network stability and quality of service, andits implementation is critical to the success of zerotouch operations.
To achieve automated recovery by NW-AI, it isnecessary for NW-AI to learn a large amount of performance data and log data during failures. ThisNTT Technical Review

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enables it to acquire the ability to respond to various
failure scenarios and respond to a failure quickly andefficiently when it occurs.
However, it is difficult to collect sufficient data on
unexpected failures that occur under conditions thatdeviate from the general operating range because
they occur infrequently; as a result, it is difficult totrain NW-AI to respond appropriately to these failures. Unexpected failures can take a long time torecover and have a serious impact on users because
recovery procedures have not been established.
Unexpected failures occur under conditions that deviate from the general operating range, but it is impractical to manually search for such conditions due to theenormous amount of time and effort required.
To address these issues, NTT laboratories areengaged in research and development to achieveadvanced coordination between verification andoperation. Specifically, by combining a network digital twin environment and chaos engineering tools thatenable artificial failure injection, NTT laboratories
have established a framework in which NW-AI canautonomously continue to learn how to handle various failures. In this framework, the chaos engineering
tool is run in a digital twin environment to generatevarious types of failures, and NW-AI learns how to
respond to them. This process can be automated overa long period to generate an enormous number of33

Feature Articles

failures, enabling the collection of data on failuresthat would not occur in normal operations. Therefore,
NW-AI can evolve to minimize unexpected failures
by increasing the number of network failures it canhandle.
2. Concept of the
NW-AI self-evolving framework
The concept of the NW-AI self-evolving framework is shown in Fig. 1. The framework creates adigital twin environment that mimics a real-world
network and artificially injects failure conditions into
the environment to collect failure data necessary for
NW-AI training. Chaos engineering tools are used togenerate these failure conditions.
Chaos engineering is an experimental approach to
improving the durability of a system by finding andcorrecting system weaknesses. This is done by intentionally causing failures in the system and observing
the results. The goal with this approach is to understand how the system responds to unexpected problems and failures, thereby identifying and correcting
system weaknesses. Chaos engineering tools aresoftware that automate and manage this process.
A chaos engineering tool allows NW-AI to collectdata on failures that rarely or never occur in real network environments by generating them in a copy
environment. NW-AI learns how to respond to failures by learning from these data.
Thus, NW-AI trained on a large amount of data canbe deployed in a real network environment to achieve
automated recovery from network failures.
3. Building an automated recovery AI using the
NW-AI self-evolving framework
Here is a step-by-step description of the process ofbuilding an automated recovery AI using the NW-AI
self-evolving framework [1, 2]. The architecture forbuilding an automated recovery AI using this framework is shown in Fig. 2.
The framework consists of an AI agent and environment, all actions of which can be automated byscripts; the AI agent and environment interact, andthe recovery strategy is built autonomously in accordance with the following steps.
(1) Failure injection
In this step, various failures are injected into thetarget system using chaos engineering tools. Failure
injection is an important process for identifying system vulnerabilities and developing countermeasures.
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Fig. 1. Concept of NW-AI self-evolving framework.

The framework injects not only failures that occur
frequently but also failures that occur infrequently
but could have a significant impact when they dooccur. This allows the system to manage a wide variety of failure situations.
(2) System-state observation
In this step, the AI agent observes the state of thetarget system and collects information about it. Specifically, the agent collects data such as various metrics and logs generated by the system over a certain
period. These data are important indicators of system
performance and status, and the agent uses them tounderstand the current state of the system and determine appropriate actions.
(3) Determine and execute recovery actions
In this step, the reinforcement learning module
determines the optimal recovery action based on
observed data and previous learning results, and therecovery action execution module executes therecovery action on the system. The recovery action isa specific action to restore the abnormal state of thesystem to normal and is determined based on theobserved data and the current system state. For example, if a failure of a particular device is observed,
restarting the device is selected as the recovery
action. On the other hand, if a problem is detected ina network route, the route is reconfigured.
(4)	Rewards based on health checks and observation of new system states
In this step, the health-check module monitors thesystem state and rewards the AI agent on the basis of
the results. Reward settings are adjusted so that thecloser the system state is to normal, the higher the
reward, so that the agent learns behaviors aimed at
normalizing the system. The health-check module’s
monitoring and reward settings provide an important
feedback mechanism for the agent to properly understand the system state and choose the optimal behavior.
34

Feature Articles

Fig. 2. Building an automated recovery AI using the NW-AI self-evolving framework.

(5) Update reinforcement learning module
In this step, the reinforcement learning module isupdated using a combination of the system state
observed by the agent, recovery action chosen,
reward obtained, and newly observed system state.
The agent stores this information and uses it as training data. Specifically, the agent learns how theselected action changed the system state and thedegree to which it led to the reward. This improves
the agent’s ability to choose actions that produce better results when similar system conditions occur.
Updating this reinforcement learning module is an
important process for the agent to understand thesystem state and its changes and choose the best
course of action. This allows the agent to continuously learn and evolve, improving the efficiency andstability of the system.

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4. Future work
We have introduced the NW-AI self-evolving
framework for developing fault-tolerant robust networks and the construction of an automated recovery
AI using this framework. In the future, we aim todevelop robust networks that are resilient to failuresby building NW-AIs that automatically execute various operations, including automated recovery, using
the NW-AI self-evolving framework.
References
[1]

[2]

H. Ikeuchi, J. Ge, Y. Matsuo, and K. Watanabe, “A Framework for
Automatic Failure Recovery in ICT Systems by Deep Reinforcement
Learning,” Proc. of 40th IEEE International Conference on Distributed Computing Systems (ICDCS 2020), pp. 1310–1315, Nov. 2020.
https://doi.org/10.1109/ICDCS47774.2020.00170
H. Ikeuchi, Y. Takahashi, K. Matsuda, and T. Toyono, “Recovery
Process Visualization based on Automaton Construction,” Proc. of
17th IFIP/IEEE International Symposium on Integrated Network
Management (IM 2021), pp. 10–18, May 2021.

35

Feature Articles

Yousuke Takahashi

Senior Research Engineer, Traffic Engineering
Research Group, Communication Traffic, Quality and Operation Research Project NTT Network
Service Systems Laboratories.
He received a B.E. and M.E. in information
science and technology from Osaka University in2007 and 2009. He joined NTT in 2009 and wasengaged in research on network management andtraffic engineering. From 2016 to 2019, he wasengaged in research on network management at
NTT Communications Corporation. He is currently engaged in research on network management using machine learning at NTT Network
Service Systems Laboratories. He received thebest paper award from the Institute of Electronics, Information and Communication Engineers(IEICE) in 2019. He is a member of IEICE.

Akio Watanabe

Senior Research Engineer, Traffic Engineering
Research Group, Communication Traffic, Quality and Operation Research Project, NTT Network Service Systems Laboratories.
He received a B.E. and M.E. in informatics
engineering from the University of ElectroCommunications, Tokyo, in 2010 and 2012. He
joined NTT in 2012 and studied optimized network management using machine-learning technologies. He is a member of IEICE.

Hiroki Ikeuchi

Researcher, Traffic Engineering ResearchGroup, Communication Traffic, Quality andOperation Research Project, NTT Network Service Systems Laboratories.
He received a B.S. and M.S. in physics fromthe University of Tokyo in 2014 and 2016. He
joined NTT in 2016. His research interest
includes application of machine learning to network operations. He received the Network Systems Research Award from the IEICE TechnicalCommittee on Network Systems and the Young
Researcher’s Award from IEICE in 2021. He is amember of IEICE.

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

36

Regular Articles

Human-behavior-understanding
Engine: Video-recognition AI Libraryfor Understanding Human Behavior
Motohiro Takagi
Abstract

To enable all many types of work to be conducted remotely as needed and overcome geographicalconstraints, NTT Human Informatics Laboratories is developing telepresence technology forunderstanding the conditions at a remote location and remotely operate an artificial body, such as a robot,
in real time. Remote operation of an artificial body requires that conditions at a remote location be
analyzed and information on operating the artificial body and on people and the environment in thevicinity of the artificial body be fed back to the operator in real time. This article introduces thedevelopment of a human-behavior-understanding engine for automatically recognizing human behavior
from camera video to recognize how people at a remote location might behave. Real-time recognition
processing is vital to providing a remote operator with feedback in real time. For this engine, wedeveloped technology for achieving lightweight recognition processing, enabling the behavior of
multiple people to be recognized in real time on a central-processing-unit-based machine.
Keywords: remote world, telepresence, video recognition

1. Telepresence technology
Due to the COVID-19 pandemic in 2020, the needarose for technology to enable various types ofremote work and overcome geographical and temporal constraints. Essential work, such as construction
and care-giving/nursing, often requires on-site
human physical operations, which makes remote
work difficult to achieve. One method of enabling
such work to be conducted remotely is to remotely
operate an artificial body, such as a robot, located at
a remote site. In remote work involving the operationof an artificial body, the operator must be able to recognize the state of the artificial body at the remotesite and the peripheral environment in real time andcarry out operations in a seamless, comfortable manner. At NTT Human Informatics Laboratories, ourgoal is to develop telepresence technology thatenables conditions at a remote site to be recognized inreal time and an artificial body to be remotely operated in a seamless and efficient manner [1]. For such
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technology to be effective, there is a need for recognition technology that can recognize the behavior of
people and the peripheral environment at the remotesite at low cost on the basis of video data obtained
from sensors such as robot-mounted cameras or surveillance cameras. This article introduces a humanbehavior-understanding engine NTT Human Informatics Laboratories developed for recognizing the
behavior of people and the peripheral environment at
a remote site by using camera video. This engine
enables lightweight recognition processing and canrecognize the behavior of multiple people in real time
on a central processing unit (CPU)-based machine. It
can also reduce the costs of generating training dataand of constructing a machine environment, which
are often barriers to introduction.
2. Human-behavior-understanding engine
featuring low-cost introduction
There has been growing interest in digital37Regular Articles

Cost factors related to model for recognizing human behavior• Time and expense of defining the requirements of behavior targeted for recognition• Time and expense of creating training data for a behavior-recognition model• Time and expense of training the behavior-recognition model…

Human-behaviorunderstanding engine
Video recognition results(information on behavior ofcustomers, employees)lRemote analysis
ofcustomer/employee behavior
Cost factors related to environment for inferring a behavior-recognition model• Time and expense of procuring a GPU-based machine• Expense of GPU instances

Examples of applicable business scenarios• Detect products picked up but not purchased torecognize customers’ interests by region not
obtainable by POS systems• Detect efficient methods of stocking shelves bycomparing employee behavior among multiple stores

Reduce costs related to construction of
behavior-recognition model and recognition environment

Fig. 1. Costs of introducing video AI for remote monitoring, etc.

transformation, particularly in technology that can
automatically analyze the behavior of people (such as
customers and employees) from video obtained fromretail stores, factories, or other sites (Fig. 1). Recognizing the behavior of people appearing in video
makes it possible to, for example, detect which products people pick up but do not purchase at a retailstore. Thus, the interests of customers, which cannot
be obtained through point-of-sale (POS) systems, canbe monitored remotely by video and needs can beanalyzed by tabulating results on a regional basis.
Such remote monitoring could also enable the analysis of efficient behavior in stocking shelves, forexample, by detecting inefficient actions of employees and comparing employee behavior among multiple stores. This type of analysis is expected to
improve customer satisfaction and employee productivity.
However, the cost of preparing the training dataneeded for creating a model for recognizing humanbehavior (behavior-recognition model) is high, whichbecomes a barrier to introducing such a model. Preparing training data requires the acquisition of a large
amount of video, extraction of behavior targeted forrecognition by visual checking, as well as the work oflabeling and annotating that video. Recognition processing often also requires the use of a graphics processing unit (GPU)-based machine, but the cost of
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constructing such a machine environment becomes
an impediment to introduction.
At NTT Human Informatics Laboratories, we haveaddressed the above issues by developing a humanbehavior-understanding engine that can shorten thetime needed for generating training data and reduce
associated expenses by presetting a pre-trained
behavior-recognition model. This engine can also
reduce the cost of constructing a machine environment by enabling operation not only using GPUs but
also CPUs.
The following are the two key points of this humanbehavior-understanding engine.
•	Point 1: Presetting a pre-trained basic-behaviorrecognition model makes additional training
unnecessary and enables recognition/searchingof behavior.
•	Point 2: Applying lightweight recognition processing within the convolutional neural network(CNN) used in the basic-behavior-recognition
model enables operation in an inexpensive
machine environment on par with CPU-based
machines.
These two points are explained below.
2.1 B asic-behavior recognition and behaviorsearching function
Our human-behavior-understanding engine
38

Regular Articles

CameraRTSP/file

Human-behaviorunderstanding
engineVideo-analysis
results
Recognize customer/employee
behavior remotely

CPU/GPU recognition

Video file

Recognize patient state remotely

Human-behavior-understanding engine

Basic-behavior recognition(walking, sitting, etc.)

Achieve basic-behavior recognition by using a state-change
function combined with an original model

Detect object (person)

PresettrainedmodelState-change recognition(change in posture, etc.)

Estimateskeleton

Estimate skeleton

TrackpersonSkeletonbased behavior
recognition

Track person

Monocular depth
Detect object
estimation
Each function can be used independently.

…

RTSP: Real Time Streaming Protocol

Fig. 2. Human-behavior-understanding engine.

incorporates an NTT-original behavior-recognition
model that can robustly recognize human behavior bydefining and recognizing a highly general, basicbehavior-recognition model common to a variety ofindustries by taking the hierarchical nature of behavior into account. Specifically, the engine first executes recognition processing of state changes, such aschanges in posture, then recognizes basic behavior
using the recognition results of those state changes(Fig. 2). The approach to basic-behavior recognition
is to define basic-behavior labels with high generality
considering the hierarchical nature of behavior andthen preset a basic-behavior-recognition modeltrained to recognize such defined basic behavior in
the human-behavior-understanding engine (Fig. 3).
A preset basic-behavior training model is constructed using training data targeting real indoor environments (obtained, for example, from convenience
store video) having relatively good lighting conditions. Given an indoor environment similar to thetraining dataset, this preset, pre-trained basic-behavior-recognition model can be used directly in its curNTT Technical Review

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rent form, so the period for constructing the model
can be reduced and expenses decreased.
It is also possible to specify important behaviors invideo through visual observation against a large
amount of accumulated video and to search for andcollect behaviors similar to those important behaviors
from a large amount of video (Fig. 4). This process
configures multiple features from video information,
distance information, and movement information
obtained from camera video and uses a combinationof those features to identify the places and times forwhich important behaviors and similar behaviors caneasily occur.
2.2 CNN model lightweight-conversion function
Some of the processing of human-behavior recognition in video is executed using a CNN, which
repeats and applies convolutional operations. Suchprocessing, however, is one factor increasing computational complexity. It achieves lightweight processing while preserving accuracy by optimizing theparameters of convolutional filters used in these39Regular Articles

Pre-trained basic-behavior-recognition model
NTT behavior-recognition dataset (indoor behavior)• Behavior labels• Person/object BBOX
• Hand area BBOX
Construction of basic-behavior-recognition model
Consolidate redundant behavior labels and create basic-behavior labels
hold

kick

Basic-behavior
detection

run standcarry sit touch
walk

have
grasp

watch push…
hold

Basic-behavior
label

crouchput down

pick uphave…

Behavior labels

Construct pre-trained basic-behavior-recognition model considering hierarchical nature of behavior
Basic behavior labels
Feature vector
Linking

Video

Convolution

Convolution

Behavior labels

Capable of recognizing
indoor behavior
with no training
required

BBOX: bounding box

Fig. 3. Basic-behavior-recognition model.

Search for similar behaviors using multiple features
Video information

Distance information(monocular depth information)

Movement information(optical flow)

Appearance feature
vectorDistance feature vector

Movement feature vector

Person behavior
database

Similar behavior

Video queryFig. 4. Behavior-search function.

convolutional operations (Fig. 5). This is done bymaking a convolutional filter sparse using the input/
output relationship of the filter as a condition on thebasis of the human visual characteristics and decreasing computational complexity by changing the filterNTT Technical Review

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application range while suppressing a drop in accuracy. Optimizing computational complexity in thismanner can also enable lightweight processing in thetemporal dimension, which in turn makes it possible
to recognize the behavior of multiple people in real
40Regular Articles

Fully connected
layer

Pooling layer

Input
3x3 filter

Convolutional filter parameters
3x3 filter

OutputOutputFilter-dilation factor…

…

Convolutional
layer

Lightweight-conversion concept

Pooling layer

Lightweight-conversion function

Basic CNN configuration
Convolutional
layer

Input

CNN configuration and parameters…

Optimize convolutional filter parameters using
the input/output relationship as a condition
Example of changing convolutional filter parameters

Filter size

Thinned-out 3x3 filter

5x5 filter

Make convolutional
filter sparse

Filter shift width

Filter-application range

Shift pixels: 1
1st filter application range

Shift pixels: 1

2nd filter application range

Shift pixels: 2

Change filter
application range
1st filter application range

Expand input by zero padding, etc.

2nd filter application range

Fig. 5. Achieving lightweight recognition in a CNN.

time even on a machine with no GPUs.
3. Summary and future developments
We have reduced the costs of creating training dataand constructing a machine environment by loading a
pre-trained basic-behavior-recognition model in anengine and making CNN-recognition processing
lightweight. For basic-behavior recognition in anindoor environment, this engine makes it unnecessary to collect video data for training purposes andassign labels at the time of introduction or to train abehavior-recognition model. It also enables the basic
behavior of multiple people to be recognized in real

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time on a CPU-based machine. For future research,
we plan to achieve the recognition of composite
behavior composed of series of operations such as
product replacement, which can be useful in work
analysis, by combining the basic behavior or objects
recognized by our human-behavior-understanding
engine with interaction information. By enabling therecognition of composite behavior described in work
manuals with such titles as “stocking the shelves withproducts in a retail store,” we will promote researchand development that will make it easy to use humanbehavior-understanding technology in work analysis(Fig. 6).

41

Regular Articles

Example of analyzing work conditions of convenience store employees
Design and installin a businesscompany
Compositeaccording to work behavior
requirements

Procedure, seriesof operations(product replacement)

Apply to identifying composite behavior using state-change andbasic-behavior functions
Object detection

Person tracking

Pastries

Skeleton-based
behavior recognition

Hold

Employee
Product replacement in progress
Apply

Basic
behavior

Smallest unit of action(walking, sitting, etc.)

Statechanges

Changes in physical state(changes in finger orientation,changes in posture)

Achieve a function for a basic behavior layer by using a statechange function combined with an original model
Skeleton-based
behavior recognition

Preset as a
pre-trainedmodel
Estimate skeleton

Track person

Detect object

Monocular depth
estimation…

Fig. 6. Composite behavior recognition tailored to usage scenario.

Reference[1]

S. Kondo, D. Sato, M. Goto, M. Takagi, and N. Matsumura,“Telepresence Technology to Facilitate Remote Working with Human
Physicality,” NTT Technical Review, Vol. 20, No. 11, pp. 27–32, Nov.
2022. https://doi.org/10.53829/ntr202211fa3

Motohiro Takagi

Senior Research Engineer, NTT Human Informatics Laboratories.
He received a B.E., M.E., and Ph.D. from Keio
University, Kanagawa, in 2009, 2011, and 2020and joined NTT in 2011. His research interests
include human-behavior understanding throughmachine learning, computer vision, and natural
language processing.

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42

Regular Articles

Low-latency Function-dedicated
Network Providing Sustained andStable Services
Tomoya Hatano, Yoshihito Sakai, Kota Asaka,
and Tatsuya Shimada
Abstract

NTT is investigating a function-dedicated network (FDN), which consists of a combination of opticaland wireless networks with edge computing, to provide services meeting various network requirements
simultaneously on the same infrastructure. NTT Access Network Service Systems Laboratories has been
researching and developing a low-latency FDN to achieve continuous and stable service provision bymeeting the service-performance requirements of low latency and low jitter. This article provides an
overview and features of our low-latency FDN.
Keywords: low latency, stability, edge computing

1. Introduction
1.1 L
 ow latency and stability of communication
services
In March 2023, the NTT Group began offering the
All-Photonics Network (APN) Innovative Opticaland Wireless Network (IOWN) 1.0 service as a firstrelease of IOWN, which is the next-generation communication infrastructure promoted by the NTT
Group. By providing the APN, which exclusively
uses the optical wavelength in all sections of the network, low latency and low jitter will be achieved, andadvanced remote work, such as remote surgery,remote ensemble, and remote control, will become
possible.
For remote control to become widespread, it is necessary to shorten the end-to-end (E2E) latency fromthe operator terminal to the controlled device andreduce the latency and jitter not only in the opticalnetwork section but also in the radio section. Remotecontrol with high accuracy requires sensitive operation, and there is a considerable possibility that misoperation may lead to a serious accident. Therefore, itis necessary to provide a stable E2E communication
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service by handling device outage and high-loaded
processing. In remote surgery, for example, theguidelines prepared by the Japan Surgical Society
indicate performance requirements of the communication environment such as latency and stability [1].
1.2 Added value for remote control using edge
computingCommunication services have traditionally beenrequired to connect separate sites and provide low
latency and high bandwidth with low error. The APN
is important for achieving this. Our low-latency
function-dedicated network (FDN) includes the APN
and a wireless network as well as computing resources, which enable data transmission from the data
source to the destination via computing resources
with data processing [2]. Our low-latency FDN provides specific communication services to users byexecuting appropriate data processing and controlling E2E service quality in accordance with serviceperformance requirements. For remote control, it ispossible to enhance controllability by assisting theoperator. For example, augmented reality images,
such as of the operation procedure or details, and43

Regular Articles

High-speed closed-loop control
technology for network &computing resources
Network
qualityServerstatusHigh-speed switching between edge
server and network simultaneously
during quality degradation--> Stable low-latency services
Servercontrol

Apps
Edge server

Remote operation
info. such as visualand haptics

Network
control
Send with assist
information

Advanced remote control

Route 1

Dronecontrol
signalAPN

Control signal

Apps

Wireless
info.

Edge server

Wired network
control

Optical-wirelesscooperative-control
technology

Route 2

Shaping in mobile backhaul (MBH) sections--> Low jitter

Fig. 1. Low-latency FDN.

Stability control(route switching)

Low-latency
control

Latency

Before control

Usingroute 1Serviceperformancerequirement
Immediate switching
to route 2

After control
Time

Fig. 2. Low latency and stability.

alarm notifications, can be displayed to the operator,
enabling smooth operation.
2. Low-latency FDN
Our low-latency FDN monitors the total transmission time of the network and processing time of edge
computing, always maintains low latency and low
jitter according to service-performance requirements,
and provides continuous and stable communication
services [3]. The following are the elemental technologies of our low-latency FDN (Fig. 1).
(1)	Optical-wireless cooperative-control technology: Technology for advanced network control by having wireless and wired sections
cooperate to achieve stricter service-perforNTT Technical Review

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mance requirements.
(2)	High-speed closed-loop control technology
for network & computing resources: Control
E2E latency to always meet service-performance requirements to ensure service stability.
Figure 2 shows the difference between low latency
and stability. Current low-latency technologies shorten the latency during normal operation and lower the
dotted line of the graph shown in the figure. An
example is lower-transmission-delay technology
such as the APN or rapid processing of edge computing. Stability, on the other hand, means quickly
returning communication service to normal byswitching over the route including network and computing resources when quality degradation occurs
due to failure, overload, etc. and shortening the time44Regular Articles

BackhaulFronthaul

eCTI

CU(vCU)/DU(vDU)

Analyze the scheduling information obtained witheCTI and control the layer-2 function.

Layer-2functionUE

Controller

APN-G

RU

Uplink transmission
APN-G: APN gateway
CU: central unit
DU: distributed unit
RU: radio unit

UE: user equipment
vCU: virtual CU
vDU: virtual DU

Fig. 3. eCTI overview.

in which service-performance requirements are notmet. It moves the dotted line to the left in the graph in
the figure.
3. Optical-wirelesscooperative-control technology
Our low-latency FDN will meet the service-performance requirements of low latency, low jitter, andstability for E2E services including a wireless section.
A mobile system that provides wireless connectionuses a wired network as a transport network for connection between base stations and the core network.
However, mobile systems and transport networks
have been designed, constructed, and operated separately and have not been integrated so that the transport network cannot be operated in accordance withthe state of the mobile system.
Cooperative dynamic bandwidth allocation (CODBA) and cooperative transport interface (CTI),
which have been studied for mobile application of
optical-access systems, are being investigated toenable a mobile system to cooperate with a transport
network.
When using optical-access systems as transport
networks for mobile systems, it is necessary to reduce
the latency of the optical-access system because thelatency allowed by the mobile system is very short.
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Therefore, CO-DBA, a function to reduce latency bydetermining the data-transmission time of opticalaccess systems in cooperation with mobile systems,
was incorporated into the International Telecommunication Union - Telecommunication Standardization
Sector (ITU-T) G.989 series of recommendations [4]that defines Next Generation Passive Optical Network 2 (NG-PON2) and the ITU-T G.9804 series ofrecommendations [5] that defines Higher Speed
PON. The interface between a mobile system andoptical-access system for exchanging informationnecessary for CO-DBA operation was also specified
as CTI in the Open Radio Access Network (O-RAN)
Working Group (WG) 4 [6].
We are investigating Extended CTI (eCTI) to satisfy the strict service-performance requirements
required for future networks by enabling cooperation
between mobile systems and optical-access systems
achieved with CTI (Fig. 3).
When implementing high-precision remote control
and automatic operation of robots, it is necessary to
reduce jitter, which has not been specified as a performance requirement in conventional networks, withina certain time because stable control becomes difficult when packet-arrival-time fluctuations are large.
The APN, which is a component of IOWN,
achieves low latency and low jitter by transmitting as
much of the wired section as possible in the opticalstate. As shown in Fig. 4, the packet-transmission
45

Regular Articles(a) Waiting for uplink transmission in TDD
Uplink5

4

Downlink

Uplink3

2

1

No uplink transmission during downlink transmission

Time(b) Transmission per transport blockTransport Block

5

4Transport Block

3

2

1
Time

Jitter generation due to transmission per transport block(c) Retransmission control
ReTx

5

4

3

Rx failure

32

Jitter generation due to packet retransmission

1
Time

ReTx: retransmission
Rx: receive
TDD: time division duplex

180
160
140
120
100
80
60
40
20
0

14
Jitter reduction(reduction rate: up to 93%)
Conventional (w/o shaping)
Proposed (w/ shaping)

0 100 200 300 400 500 600 700 800 900 1000
Application traffic rate [Mbps]

Average latency [ms]Average jitter [µs]Fig. 4. Causes of jitter in radio sections.

12
10
8
6
4

Latency degradation by applying
our low-latency FDN (less than 1 ms)
Conventional (w/o shaping)
Proposed (w/ shaping)200 100 200 300 400 500 600 700 800 9001000
Application traffic rate [Mbps]

Fig. 5. Jitter reduction by applying optical-wireless cooperative-control technology.

interval in the radio section varies due to the transmission-waiting time and retransmission control.
The optical-wireless cooperative-control technology enables various performance improvements
through the cooperation of wireless and wired sections. We have shown that jitter can be suppressed by
up to 93% with this technology [7] (Fig. 5) by sharing
information on transmission timing and transmission
amount in the wireless section from the mobile system to transport network, analyzing this information,
NTT Technical Review

Vol. 21 No. 12 Dec. 2023

and controlling the equipment that constitutes thetransport network.
This technology is under discussion as a work itemof the IOWN Global Forum and is described in thetechnical document published by the Forum [8].
4. High-speed closed-loop control technology for
network & computing resources
Even when communication services combining
46

Regular Articles

Network controller
Collection of
networkstatuses
Collection ofserverstatuses

Control of
networkswitching• Measuring E2E delay• Determing the need toswitch over
• Determining theswitchover destination

Control ofserverswitchingComputing-resource controller

SwitchSwitchSwitchover

SwitchSwitchFig. 6. High-speed closed-loop control technology for network & computing resources.

network and edge computing are provided, quality
control is carried out in both network and edge computing separately. Therefore, quality degradation ofservices, which does not have a critical degradation
point, cannot be detected and might continue todegrade.
To solve this problem, we are researching anddeveloping a high-speed closed-loop control technology for network & computing resources that enables
the network and server to cooperate (Fig. 6). This
technology is made possible by rapidly automating
three elements: (1) collection of network informationand computing-resource information, (2) analysis of
the collected information, and (3) control in the eventof quality degradation by having the network controller and computing-resource controller cooperate.
4.1 Accelerated collection, analysis, and control
and cooperation of controllers
By executing the collection, analysis, and control
cycle from the occurrence of degradation to thecompletion of the action at high speed, the service
provider can recover quality degradation in a shorttime.
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Vol. 21 No. 12 Dec. 2023

(1)	Collection: Collect network-latency information by using high-speed telemetry and computing-resource processing time by analyzing
data before and after processing using edge
computing to calculate E2E latency.
(2)	Analysis: Determine if the E2E latency meetsthe service-performance requirements, and if
not, determine the need to switch over to analternate route. When switching, the systemdetermines the switching destination after
confirming that the latency satisfies the service-performance requirements in consideration of the new route of the network andcomputing resources.
(3)	Control: Switch the network and computing
resources to a determined destination. The
switch timing is controlled to minimize theimpact on the service.
For collection, analysis, and control, the network
controller and computing-resource controller mustcooperate. During collection, cooperation is needed
to calculate E2E latency, and during analysis, cooperation is needed to discover and calculate the newavailable resources of network and computing that47

Regular Articles

YokosukaMusashino

Fig. 7. Demonstration experiment.

meet the service-performance requirements. Duringcontrol, cooperation is needed when the switchingtime is adjusted.
We implemented our low-latency FDN with devices such as optical switches and servers and confirmedthat the collection, analysis, and control time related
to switching was kept within 90 ms [9].

which provides continuous and stable service bymeeting the service-performance requirements oflow latency and low jitter, and its demonstration
experiment. We will further reduce the latency of thewireless section and provide E2E stability by using
eCTI to take into account the traffic characteristics of
the wireless section.

4.2 Demonstration of remote control
To confirm the effectiveness of our low-latency
FDN, we deployed a display and robot operationequipment at the NTT Musashino R&D Center and arobot arm and edge server at the NTT Yokosuka R&D
Center and constructed an experimental network forremote control by connecting the two sites withapproximately 150 km of optical fiber [10] (Fig. 7).
At the site with the robot arm, there was a network
camera and haptics sensor, and the haptics information was converted into visual information on theedge server. The operator controlled the robot arm
remotely through visualization of the haptic information (Fig. 7).
When the remote-control environment deteriorated
due to overloading of the edge server, remote control
became difficult in the conventional configuration
without our low-latency FDN. However, with our
FDN, remote control could be executed without incident by completing switching control about 100 ms
after quality deterioration and by transmitting haptics
information. Therefore, the effectiveness of our lowlatency FDN was confirmed.

References

5. Future outlook
This article introduced our low-latency FDN,
NTT Technical Review

Vol. 21 No. 12 Dec. 2023

[1]
[2]
[3]
[4]
[5]
[6]
[7]

[8]

[9]

Japan Surgical Society, “Guidelines for Telesurgery,” June 2022 (inJapanese), https://jp.jssoc.or.jp/jss122/remote20220427.pdf
A. Kawabata and Y. Aoyagi, “Network-service Technology Enabledby the All-Photonics Network,” NTT Technical Review, Vol. 19, No.
10, pp. 18–24, Oct. 2021. https://doi.org/10.53829/ntr202110fa1
T. Yoshida, “Low-latency and Energy Efficient Technologies for New
Optical Access Networks,” NTT Technical Review, Vol. 21, No. 9, pp.
48–51, Sept. 2023. https://doi.org/10.53829/ntr202309fa7
ITU-T, G.989: “40-Gigabit-capable passive optical networks(NG-PON2): Definitions, abbreviations and acronyms,” Oct. 2015.
ITU-T, G.9804.1: “Higher speed passive optical networks –Requirements,” Nov. 2019.
O-RAN ALLIANCE, O-RAN-WG4.CTI-TCP.0-v02.00: “O-RAN
Fronthaul Cooperative Transport Interface Transport Control Plane
Specification 2.0,” Mar. 2021.
K. Miyamoto, Y. Sakai, T. Shimada, and T. Yoshida, “Mobile
Backhaul Uplink Jitter Reduction Techniques with Optical-WirelessCo o p e r a tiv e Co n tr o l, ” 2 0 2 2 2 7 th O p to Ele c tr o n i cs andCommunications Conference (OECC) and 2022 International
Conference on Photonics in Switching and Computing (PSC),
Toyama, Japan, 2022, pp. 1–4, 2022. https://doi.org/10.23919/OECC/
PSC53152.2022.9850132
IOWN Global Forum, “Technical Outlook for Mobile Networks
Using IOWN Technology - Advanced Transport Network Technologies
for Mobile Network,” Apr. 2023.
https://iowngf.org/wp-content/uploads/formidable/21/IOWN-GFRD-IMN-PHSE2-1.0.pdf
H. Ou, C. Huang, T. Hatano, K. Asaka, T. Shimada, and T. Yoshida,“First Demonstration of Cross-domain Real-time Control between
Networks and Computing Resources Utilizing Cooperative SLA
Analysis,” Proc. of 49th European Conference on OpticalCommunications (ECOC 2023), We.B.5.4, Glasgow, Scotland, UK,
Oct. 2023.

48

Regular Articles[10] NTT press release, “NTT and Mitsubishi Electric demonstrate remoterobot operation enhanced by network-server cooperative control
technology–Conversion of haptic information into visual information

Tomoya Hatano

Senior Research Engineer, NTT Access Network Service Systems Laboratories.
He received a B.E., M.E., and Ph.D. in communication engineering from Keio University,
Tokyo, in 2002, 2004, and 2007. In 2004, hejoined NTT Access Network Service Systems
Laboratories. He is currently engaged in the
research and development of optical communication systems and network virtualization. He is amember of the Institute of Electronics, Information and Communication Engineers (IEICE).

Yoshihito Sakai

Senior Research Engineer, NTT Access Network Service Systems Laboratories.
He received a B.E. and M.E. in electrical andelectronic engineering from Tokyo Institute ofTechnology in 2003 and 2005. In 2005, he joined
NTT Access Network Service Systems Laboratories, where he was engaged in research anddevelopment on next-generation optical-accessnetworks and systems. Since 2020, he has beenworking on optical networks for mobile systems.

enabled simple device configuration,” May 16, 2023.
https://group.ntt/en/newsrelease/2023/05/16/230516a.html

Kota Asaka

Senior Research Engineer, Optical Access
Systems Project, NTT Access Network Service
Systems Laboratories.
He received a B.S. and M.S. in electrical engineering from Waseda University, Tokyo, in 1996
and 1999 and Ph.D. in physics from Kitasato
University, Tokyo, in 2008. He joined NTT Photonics Laboratories in 1999 and investigatedsmall optical subassemblies for access networks.
Since 2012, he has been with NTT Access Network Service Systems Laboratories, where he isresearching and developing next-generation
optical-access networks. He has contributed toseveral standardization/open source softwareorganizations, including International Electrotechnical Commission (IEC) SC86C/WG4,
ITU-T Q2/SG15, Full Service Access Network(FSAN), Open Networking Foundation (ONF),
and Broadband Forum (BBF). His recent activities have focused on the development of disaggregation technologies in access systems. He
also served as a member of the SDN Enabled
Broadband Access (SEBA) Reference Design
Team at ONF and as the project stream leader for
the PON Abstraction Interface for Time-Critical
Applications (TR-402 and 403) at BBF. He is amember of the Institute of Electrical and Electronics Engineers (IEEE) and IEICE.

Tatsuya Shimada

Senior Research Engineer, Supervisor, NTT
Access Network Service Systems Laboratories.
He received a B.E. in applied physics fromTohoku University, Miyagi, in 1997 and Ph.D. inengineering from Hokkaido University in 2009.
He joined the NTT Multimedia Systems Development Center in 1997, where he developed
asynchronous transfer mode optical-access systems. In 1999, he moved to NTT Access Network
Service Systems Laboratories and has been
investigating wavelength-division-multiplexing
optical-access networks and systems since 2000.
From 2005 to 2008, he was with NTT EAST andengaged in the sales promotion of optical network services. He has been investigating an
optical network for the fifth-generation mobile
communication system and future mobile systems. He is a member of IEICE.

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

49

Global Standardization Activities

Report on the Second Plenary
Meeting of ITU-T SG2
Standardization of
Telecommunication Numbering
Koji Isshiki and Mariko Honda
Abstract

The second plenary meeting of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) Study Group (SG) 2 for the 2022–2024 study period was held virtually fromMarch 13th to 22nd, 2023 with 137 participants from 42 countries. SG2 consists of Working Party (WP)
1, which standardizes numbers and identifiers, and WP2, which standardizes network management. In
this article, we report on the status of WP1. As telecommunications services progress, SG2’s activities
related to numbers and identifiers have become broader. We categorize them into nine issues and reporton the status of activities for each issue.
Keywords: telecommunication numbering, international mobile subscriber identity, telephone number
mapping

1. Issues addressed by Working Party 1
The issues addressed by Working Party (WP) 1 ofthe International Telecommunication Union Telecommunication Standardization Sector (ITU-T)
Study Group (SG) 2 can be classified into (1) Numbering plan, (2) International mobile subscriber identity (IMSI)/subscriber identification module (SIM)related, (3) Proper use of numbers, (4) Number-recommendation maintenance, management, and allocation, (5) Porting/switching, (6) Interworking, (7)E.164 Number Mapping (ENUM), (8) Disaster calls/
emergency calls, and (9) Others. We report on thestatus of the activities for each issue.
1.1 Numbering planThis category involves creating a numbering planfor international telecommunications services andcreating various regulations such as requirements forallocating number resources.
In the previous study period, SG2 created the new
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Vol. 21 No. 12 Dec. 2023

work item E.IoT-NNAI (see Table 1) to define andallocate Internet of Things (IoT) numbers to copewith the worldwide rapid increase in the use of numbers for IoT services. Initially, consideration wasmade with eCall as the main use case, which allows
vehicles to use emergency call services no matter
where they are located in Europe, and a basic number
structure proposal has already been submitted. However, before waiting for E.IoT-NNAI to become arecommendation, many international network operators aiming to provide global IoT services use existing international numbers (International ITU-T
E.164-number for Networks). At the interim meeting(held in July 2023) after the second SG2 plenary
meeting, a proposal was submitted suggesting thatthe existing international network numbers startingwith 883 be redefined as IoT numbers in a mannerconsistent with the services already introduced. The
limit of the international number length is up to 15
digits. Therefore, the main issue of this change is how
to reuse the international numbers for existing50

Global Standardization Activities

Table 1. List of draft recommendations (WP1 related).
Grouping

Recommendation
numberNumbering plan

E.IoT-NNAIE.212

IMSI/SIM related

Proper use of
numbers

Numberrecommendation
maintenance,
management, andallocation

Internet of Things Naming Numbering Addressing and Identifiers
The international identification plan for public networks and subscriptions

E.118

Editor’s country
UK—(No issues currently
under consideration)

The international telecommunications charge card

Italy

E.118.1 (E.GAIN)

ITU-T Management of the allocation of globally assigned Issuer Identifier
Numbers (IINs)

UK

E.156

Guidelines for ITU-T action on reported misuse of ITU-T E.164 number
resources

India

TR.MMWF

Methodologies to Mitigate Wangiri Fraud

Sudan

TR.OTTnum

Current use of E.164 numbers as identifiers for OTTs

UAE, USE.ACP

Alternative calling procedures

Egypt

TR.PCM

Permitted call masking

Egypt

TR.SPN

Spoofing using national number

Egypt

E.164.1

Criteria and procedures for the reservation, assignment, and reclamationof E.164 country codes and associated identification codes (IC)

UK

E.190

Principles and responsibilities for the management, assignment andreclamation of E-series international numbering resources

UK

ITU-T E.Global NNAI Assignment Processes

UK

Mechanisms and processes for audits of the assignment of global
naming, numbering, addressing and identification processes

UK

E.164
Supplement 2

Number Portability

Japan

TR.CarrierSwitching

Carrier Switching

UK, India

E.1120 (E.gap)
E.AuditPorting/switching

Recommendation title

Service principles when public circuit-switched international
telecommunication networks interwork with IP-based networks

Egypt

E.ENUMINF

Differentiating between ENUM and Infrastructure ENUM

UAE

Not yetdetermined

Artificial Intelligence for Natural Disaster Management (anonym)

Interworking

E.370

ENUM
Disastercalls/emergency
calls

networks while using previous studies that haveenabled the number capacity for IoT numbers to be
secured and various services to be selected. The next
discussions are scheduled to take place at the third
plenary meeting in November 2023.
1.2 IMSI/SIM relatedThis category includes IMSI, which identifies subscribers of mobile phone terminals, and issuer identifier number (IIN), which identifies SIM card issuers.
1.2.1 IMSI issues
IMSI is assigned on the basis of the provisions ofRecommendation E.212 (the international identification plan for public networks and subscriptions) andis written to the SIM of a mobile phone. Regarding
IMSI, which takes global IoT into account, the issueof how to expand capacity was discussed in the previous study period within the constraints of the IMSINTT Technical Review

Vol. 21 No. 12 Dec. 2023

Germany (FGAI4NDM Chair)length, which is a maximum of 15 digits, like theinternational number length. Options for capacity
expansion included no changes, format extensions,
new non-backwards compatible schemes, and hexadecimal coding. However, it is expected that implementation of capacity expansion will be difficult, andalthough it is difficult to accurately predict the future
increase in IoT services, it was determined that there
is currently a large number of resources available for
new applications. Therefore, it has been decided that
there will be no change, and that usage will be analyzed at every SG2 meeting.
1.2.2 IIN assignment
In this study period, SG2 focuses on examining IIN
issues. IIN is the issuer number of the SIM card andassigned on the basis of the provisions of Recommendation E.118 (see Table 1). IIN complies with International Organization for Standardization/International
51

Global Standardization Activities

Electrotechnical Commission (ISO/IEC) 7812 card
regulations, and the major industry identifier is anumber starting with 89, which is specified for telecommunications purposes. IINs had been allocatedby each country’s numbering authority, but with thedevelopment of global services, it is now necessary to
directly allocate IINs for global use from the Telecommunication Standardization Bureau (TSB), so
Recommendation E.118.1 (see Table 1) was created
and approved at the second plenary meeting.
Regarding Recommendation E.118, a revised draftthat incorporates the latest information was proposedat the interim meeting (held in July 2023), and discussions are scheduled for the third plenary meeting inNovember 2023.
1.3 Proper use of numbers
This category involves proper number usage to deal
with the misuse of numbers. Most contributions submitted to SG2 are related to this issue. With the shift
to Internet protocol (IP) networks and the increase inover-the-top (OTT) services, problems such as calling-number spoofing and unauthorized call-routingchanges aimed at changing billing are occurring frequently on an international basis. In particular, there
has been an increase in the number of contributions
submitted from developing countries, which havesuffered a lot of harm, and this has become one of themost important issues for SG2.
1.3.1 Number-misuse reporting guidelines
This issue involves the revision of Recommendation E.156 (see Table 1), which stipulates the procedure for reporting to the TSB and the guidelines foractions to be taken by the TSB when problems causedby misuse of number resources occur. At the firstplenary meeting in May 2022, improvements to themisuse-report form and consistency with Resolution
61 (Countermeasures against misuse of international
numbers) were discussed, and editors from India continued to discuss the baseline texts. Suggestions werealso made to update the text description, and the draft
recommendation was revised accordingly.
1.3.2 Wangiri countermeasures
This issue involves the formulation of a technicalreport, TR.MMWF (see Table 1), which examines
countermeasures against Wangiri fraud. The goal wasto reach an agreement at the second plenary meeting,but the distributed ledger technology platform, one of
the 18 items listed as countermeasures, was determined to be reconsidered from the perspective ofquick response. Comments were also made regarding
consistency of the content as a whole should be
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Vol. 21 No. 12 Dec. 2023

achieved, and that editorial corrections such as theunification of abbreviations are needed. Therefore,
the agreement was postponed until the next plenary
meeting.
1.3.3 Using E.164 numbers for OTTs
The use of numbers in OTT services is also included in the appropriate use of numbers, and the technical report TR.OTTnum (see Table 1) on how to use
E.164 numbers as identifiers in OTT services is being
considered. At this meeting, progress was madetoward completion on the basis of the output documents from the drafting meeting held in January2023.
To advance the consideration of this issue, NTT
submitted a contribution classifying use cases for theuse of E.164 numbers for OTTs at the first and second
plenary meetings. While there was an opinion that it
was beyond the scope of this technical report, there
were also opinions that the content was extremely
useful and should be used. In response, at the interim
meeting (held in July 2023), NTT proposed the use of
the content in new work items. It was also agreed tocontinue discussions on the relationship with existing
work items, etc. in preparation for the third plenary
meeting in November 2023.
1.3.4 Selective-call setup procedure
This issue involves the creation of a new recommendation, E.ACP (see Table 1). Alternative calling
procedures (ACP) are different international connections from normal public switched telephone network/public land mobile network (PSTN/PLMN)
interworking. ACP uses, for example, OTT applications, interworking with IP networks, SIMboxes, andinternational callbacks. It is a form of communicationthat significantly degrades quality of service/qualityof experience and performance. Due to internationalrouting being executed using ACP using a different
route than usual, many problems have arisen in whichinternational charges are different from those agreed
upon internationally. At this meeting, a contribution
was submitted from the UK, which pointed out that
the ACP that is invalidated differs depending on theregulations of each country. From this perspective, it
was agreed that E.ACP should include a requirement
to notify the TSB of each country’s views and makethe information public on bulletin boards, etc.
1.3.5 Other issues
There was a proposal from Sudan stating that reexamination is necessary on TR.SPN approved in
2021 (see Table 1) from the viewpoint of whether it
includes, for example, neighbor spoofing using numbers in the vicinity of the called user. In response to52

Global Standardization Activities

this, it was decided to proceed with the revision process, and requests were made to submit contributions
with information on the status of spoofing in eachcountry.
The issue of permissible call masking is targeted
for preparation in the technical report TR.PCM (seeTable 1), but there was no discussion at this meeting.
1.4 N umber-recommendation maintenance,
management, and allocation
This category involves revising the recommendations necessary for number assignment, etc. Althoughmany recommendations are being reviewed, the following two issues are of particular interest.
1.4.1 Integration of global NNAI-allocation-process description
This issue involves the creation of a new recommendation, E.gap (see Table 1). From the perspectiveof ease of understanding number application andallocation procedures, collection of process descriptions in one place is done from related recommendations E.164, E.212, E.118, E.118.1, and E.218. This
draft recommendation was approved for Determination at this meeting and given Recommendation
Number E.1120, and is scheduled to be approved as arecommendation at the third plenary meeting after
going through the Traditional Approval Process consultation.
1.4.2 Audit after international-number-resource
allocation
This issue involves the creation of a new recommendation, E.audit (see Table 1). E-series number
assignment is based on Recommendation E.190 (seeTable 1), but there was no recommendation that stipulated number management after assignment. Therefore, the creation of a new work item with the aim of
stipulating the implementation of audits of the usage
status of number resources by TSB or ITU-T SG2
number experts in light of the number-resource-allocation requirements was approved at this meeting.
1.4.3 Other issues
At the interim meeting (held in July 2023), discussions regarding the revision of Recommendation
E.190 (see Table 1), which stipulates principles andresponsibilities of the management, allocation, andreuse of international number resources were madeand planned for discussion at the next plenary meeting.
1.5 Porting/switchingThis category involves the revision of E.164 Supplement 2 (see Table 1) regarding number portability.
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This category also involves the creation of TR.Carrier-Switching (Table 1), which stipulates proceduresfor changing carriers (carrier switching) by IoT service providers.
At the interim meeting (held in July 2023), NTT,
the editor of E.164 Supplement 2, submitted a contribution to consider number portability in IoT services.
This proposal is considered useful for the revision of
E.164 Supplement 2 and creation of E.IoT-NNAI,
and it will continue to be discussed at the third plenary meeting in November 2023.
Regarding TR.Carrier-Switching, the UK and India
are currently working as editors, but there was no
discussion at this meeting, and contributions wererequested for the next meeting.
1.6 Interworking
This is a category that stipulates service principles
when interconnecting public-switched international
telecommunications networks and IP-based networks
and aims to revise Recommendation E.370 (see Table
1).
This is a recommendation regarding services wheninternational networks, such as PSTN, integrated
services digital network (ISDN), and PLMN, interwork with IP-based networks, and revision work isunderway. At this meeting, there was a discussion onwhether the notation “OTT” should be included in therevised draft of E.370 regarding the structure of international networks, and it was decided to continue thediscussion at the third plenary meeting in November
2023.
1.7 ENUM
This category stipulates ENUM, a function thatmaps telephone numbers and Internet addresses.
The main study issue is to create a new recommendation, E.ENUMINF (see Table 1). The goal is tocreate a clear description for differentiating the original ENUM from Infrastructure ENUM (ENUM-likefunction), which are being confused in discussions byother SGs.
Another issue with ENUM was raised by Réseaux
IP Européens Network Coordination Centre (RIPE
NCC), which operates ENUM’s top-level domain tier0 (e164.arpa). Since we received a report from RIPE
that only 35 of the 59 tier 1 allocations at the member
country level are operated normally, we have decided
to check the operating status of ENUM to understandthe situation in the countries concerned. The TSB
prepared a draft letter asking the authorities to report
the operating status of ENUM and decided to proceed53

Global Standardization Activities

with the discussion at the third plenary meeting inNovember 2023.
1.8 Disaster calls/emergency calls
Current activities in this category include the Focus
Group on Artificial Intelligence for Natural Disaster
Management (FG-AI4NDM), which is a group under
SG2 that is examining ways to use artificial intelligence (AI) to strengthen resilience from natural
disasters.
FG AI4NDM was established under SG2 in
December 2020. At this meeting, due to the impact of
the coronavirus pandemic on the progress of discussions, it was decided that FG-AI4NDM activities be
postponed until March 2024. However, at this meeting several study results were submitted as a formal
outcome document. In particular, WG (Work Group)Comms reported “Communication systems and bestpractices that utilize AI” and “Best practices for
applying AI to communication systems for NDM” aseffective communication methods using AI for natural disaster management (NDM). In addition to thesebest practices, technical studies of specific use cases
are progressing in preparation for the final report. As
the application of AI to disaster management will begetting more active in each country, attention should

Koji Isshiki

Professional Staff, Network Innovation Business Headquarters, NTT Advanced Technology
Corporation.
He joined NTT Advanced Technology Corporation in 2001 after he had been engaged in the
research and development of voice and dataswitching systems at the research, business, andinternational business sections at NTT. Since
then he has been engaged in the investigation andstandardization of telecommunication numbers
and related technologies by attending ITU-T
SG2, Internet Engineering Task Force (IETF),
European Telecommunications Standards Institute (ETSI), and CEPT ECC Working Group
Numbering and Networks (ECC-NaN) and byvisiting Numbering NRAs in the US and European countries for discussions every year.

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Vol. 21 No. 12 Dec. 2023

be paid to the status of the studies.
1.9 Others
Discussions regarding WTSA (World Telecommunication Standardization Assembly) resolutions areheld when issues arise, even if there is no work item
for recommendation. Activities, such as international
number allocation by Number Coordination Team
(NCT), discussion on issues from NCT reports, discussion of measures for resource scarcity in accordance with the allocation status of international number resources, and consulting and other support fordomestic numbering plans will be discussed separately from work items.
2. Conclusion
With new developments in telecommunications
services and changes in networks, the roles of numbers and identifiers are changing, and the activities of
SG2 are becoming broader. SG2 has begun considering activities for the next study period, but there arestill many issues that need to be addressed. Whileconsidering these trends, SG2 will continue to proactively promote standardization activities related tonumbers and identifiers.

Mariko Honda

Engineer, Network Innovation Business Headquarters, NTT Advanced Technology Corporation.
She joined NTT Advanced Technology Corporation in 2018. She has been engaged in ITU-T
standardization activities, especially on ITU-T
SG2 for telecommunication numbers and related
technologies.

54

Practical Field Information about
Telecommunication Technologies
Practical Field Information about Telecommunication Technologies

Case Studies in 50-bit/s Leased Lines:
Modem Communication Failure at
Earth-return Circuit and the Causeof Failure to Replace Metallic
Transmission Line with Optical Cable
Technical Assistance and Support Center, NTT EAST
Abstract

This article introduces two failure cases concerning 50-bit/s leased lines: communication failure at theearth-return circuit and the cause of failure to replace a metallic transmission line with an optical cabledue to the wrong selection of 50-bit/s leased line systems. This is the seventy-ninth article in a series ontelecommunication technologies.
Keywords: leased line, metallic-return circuit, earth-return circuit

1. Introduction
A leased line is a dedicated network service thatprovides exclusive communications between specificcustomer premises. Leased lines offer higher quality
and strict security compared with a public switched
network or other network services and are widelyused to connect internal lines between customer
premises. Various companies use leased lines formonitoring or controlling various equipment as social
infrastructures.
Leased line services provided by NTT EAST/
WEST are available for analog and digital communications. For analog communications, there are two
types of low-speed services, those that transmit voice
signal services and those that are modem or facsimile
signal services. Modem or facsimile signal services
are used for data transmission at minimum speeds as
50 bit/s.
This article presents two failure cases in which the
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Vol. 21 No. 12 Dec. 2023

Technical Assistance and Support Center (TASC),NTT EAST, provided support for 50-bit/s leasedlines: modem communication failure at the earthreturn circuit and the cause of failure to replace a
metallic transmission line with an optical cable.
2. Case studies
2.1 C ommunication failure between sewagetreatment plants
2.1.1 Equipment configuration and failure details
The first case is concerning a sewage-treatmentcompany that uses a 50-bit/s leased line to monitor
and control their pumping stations around the city.
When a problem occurs in their system and theydetect a control-error alarm from a specific pumping
station, they sometimes inquire whether NTT’s
leased line is operating normally. For such a claim,
the NTT local maintenance center tried to detect thefault point in the leased line by changing the wire of55

Practical Field Information about Telecommunication Technologies

End point: Pumping station

Start point: Control center
Customer section
Monitoring
terminal

Control-center
modem
TransTransmission

3

Customer section

NTT protective
device4

Reception
Control-error alarmat pumping station

Start-point
NTT CO

End-point
NTT CO
L2
Subscriber
cable

L1
Subscriber
cable
L2

Oscilloscope

NTT protective
device

L1

Pumping-station
modem
2

Reception

1

Trans
Trans-mission

Pumpingequipment

DSM DSM

Signal direction

Fig. 1. Equipment and measurement configuration.

the subscriber cables between the control center andpumping station. The NTT local maintenance center
also replaced subscriber-line cards installed in the
dedicated service-handling module (DSM), whichaccommodates leased lines at NTT central offices(COs). However, when the failure was not mitigated,the control center consulted TASC. In this case, thecustomer is using 50-bit/s leased line with earth
return.
The configuration of the customer’s system andNTT network (leased line) are shown in Fig. 1. To
identify the cause of the failure, it is important toclarify the type of leased line. NTT generally provides two types of transmission methods for 50-bit/s
leased lines: metallic return and earth return. A
metallic-return method involves making a closed
circuit with two wires in the line, and the direction of
the current identifies the transmission and reception.
An earth-return method involves making a closed
circuit of a cable and ground (earth) with a unidirectional line used for transmission and the other forreception.
2.1.2 I nvestigation method for failure-factor
inspection
We assumed that the control-error alarm in the customer’s equipment was caused by an error in thecommunication signal. We first decided to investigate
the voltage and current waveform conditions of thetransmission signal between the DSM and customer’sequipment. We used an oscilloscope to measure thevoltage and current of the modem signals, as shownin Fig. 1, at the control center and pumping station.
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Vol. 21 No. 12 Dec. 2023

Since this customer’s leased line using an earthreturn method, we measured the signal voltages
between L1-earth/L2-earth (2.1.3 (A)). We also measured the electrical characteristics of the on-premises
wiring (NTT section and customer section) in thecontrol center and pumping station (2.1.3 (B)).
2.1.3 Results of the investigation(A) Waveform of transmitted and received signals
The measured waveform of the transmitted signal
from the pumping-station modem (transmitted signal) and received signal from the control-centermodem (received signal) are shown in Figs. 2(a) and(b), respectively. The transmitted signal (Fig. 1 Signal direction 1 ) is formed using a bipolar encoding(i.e., 0 and 1 expressed as positive and negative) for
both voltage and current (Fig. 2(a-1, a-2)); however,
the received signal (Fig. 1 Signal direction 2 ) is
formed using a unipolar encoding (0 and 1 expressedas positive and 0A) with the negative component
missing (Fig. 2(b-2)).
On the basis of these results, we concluded that thecontrol-center modem was transmitting a normal
bipolar encoding signal. However, before reaching
the pumping-station modem, the transmitted current
signal degraded to a unipolar encoding signal (Fig. 3).
(B)	Electrical characteristics of subscriber-lines(copper-impairment test)
To confirm the normality of the metal wiring section, we also measured the electrical characteristics
of subscriber-lines, i.e., foreign voltage, capacitance,
and insulation resistance. The measurement results
were within NTT’s maintenance standards at both the56Practical Field Information about Telecommunication Technologies

20 ms/div
+50
DC
(V)

(a-1) Voltage between L1 and earth(b-1) Voltage between L2 and earth(a-2) Current L1(b-2) Current L2

0

-50
+50
DC
0
(mA)

0 mANegative component is missing.
−19.7 mANegative component is present.

-50(a) Signal transmitted from pumpingstation modem(Normal)(b) Signal received at pumping-station modem(signal transmitted from control-center modem)(Abnormal)

Fig. 2. Signal waveform measured at pumping station.

50 ms/div
+50
DC
(V)

(a-1) Voltage between L1 and earth(b-1) Voltage between L1 and earth

0

-50
+50

(a-2)
Current L1−27.9 mANegative component
is present.

DC
0
(mA)

(b-2) Current L1−2.8 mANegative component is decreased.

-50(a) Signal transmitted from control-center modem(from modem to protective device)(Normal)(b) Signal transmitted from control-center modem(from protective device to NTT CO)(Abnormal)

Fig. 3. Signal waveform measured at control center.

start and end points, and the section from the NTT
CO to the NTT protective device was normal.
Considering the results presented in sub-section(A), the control-error alarm was caused between thecontrol-center modem to the NTT protective device;
therefore, we measured the electrical characteristics,
including the customer section (the customer modem
to the NTT protective device) at the control center.
From those measurement results, the insulation resistance between L1 and earth was nearly 0 Ω; in otherwords, L1 was in the earth-fault state within the customer section.
2.1.4 Cause of failure
After identifying the suspected failure section, theNTT protective device and control-center modem
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Vol. 21 No. 12 Dec. 2023

were wired directly to bypass the other customer’sequipment. Thus, the control-error alarm no longer
occurred. As a result of the customer’s equipment
inspection of the private wiring section, it was confirmed that the customer’s arrester (surge arrester)inserted in this section was defective.
2.1.5 Conclusion
This case was not caused by NTT equipment failure
but the customer’s equipment. The customer’s arrester installed in the customer section was broken, andL1 was connected to earth, which caused the signaltransmitted from the control center to leak into earth.
The pumping-station modem (on the receiving side)
was thus unable to recognize that signal; therefore,
the control-error alarm occurred at the control center.
57

Practical Field Information about Telecommunication Technologies

Table 1. Type of subscriber-line cards and operation modes.
Subscriber-line
package in theDSM
VT1

2-wire bipolar earth-return system
2- and 4-wire bipolar
metallic-return system

VT2

VT3

Mode
name

Communication system
Full-duplex–

A

2-wire system: unidirectional
4-wire system: full duplex–

B

2-wire unipolar metallic-returnsystemUnidirectional

4-wire unipolar metallic-returnsystemBidirectional
Full-duplex

NTT
start-point CO
Start point

Power source for transmitting terminal: Yes

C1

Power source for transmitting terminal: No

D2

Power source for receiving terminal: Yes

D1

Power source for receiving terminal: No

C2

Power source for transmitting terminal: Yes

C3

Power source for transmitting terminal: No

D3

NTT
end-point CO

MDF

MDF

Relay metal
cable

L1

Modem

L1

End point
Modem

L2

L2
Oscilloscope

Replacing

DSM

ReplacingNocommunication

Measurement
point (A)Oscilloscope

DSM
Measurement
point (B)Fig. 4. Equipment configuration and failure that occurred.

2.2 C
 ommunication failure after replacing metallic transmission line with optical cable
The second case study concerns the line-replacing
failure of a 50-bit/s leased line.
2.2.1 Equipment configuration and failure details
In this case, a 50-bit/s leased line is used to transmit
data between the customer’s sites. The line connection between the two NTT COs which accommodatea 50-bit/s leased line is a metallic transmission line.
We decided to eliminate the metallic transmission
line and replace it with an optical cable using DSMs.
There are various types of 50-bit/s leased line systems, as listed in Table 1, and different subscriberline cards are used for each type. The results of aninterview with the customer revealed that they wereusing an earth-return/unidirectional communication
system for their terminals, so the NTT local service
center member selected the VT1 package as the line
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Vol. 21 No. 12 Dec. 2023

card and replaced the line. However, a communication failure occurred. Thus, TASC was asked toinvestigate the cause of the failure. The configurationof the equipment involved in this case study is shownin Fig. 4.
2.2.2 Investigation method
The cause of the communication failure after
replacing the DSMs may have been a mismatch
between the communication modes of the customer’s
modem and subscriber-line package. There are manysetting patterns for the communication mode of a
50-bit/s leased line, and the operation mode must be
set correctly after confirming the customer’s modem
communication mode. On the basis of the above, we
believed that it was necessary to confirm the operation mode on the basis of the facts, and as in case (1),
we measured the communication signal using anoscilloscope.
58

Practical Field Information about Telecommunication Technologies

100 ms/div
20

Voltage between
L1 and earth (DC V)
Voltage between
L2 and earth (DC V)

0

Same waveform with
opposite polarity

-20
20
0
-20

(a) Voltage waveform

100 ms/div
40

L1 current (mA)0-40

L2 current (mA)

Unipolar encoding, 20 mA

40
0
-40

(b) Current waveform

Fig. 5. Measurement results.

2.2.3 Results of the investigation(A) Communication mode and encoding scheme
The measurement results are shown in Fig. 5. The
voltage waveforms on L1 and L2 had opposite polarity (Fig. 5(a)), indicating that the modems use themetallic-return system. Moreover, the code polarityof both voltage and current did not change, indicatingthat the encoding scheme is a unipolar encoding witha current of 20 mA (Fig. 5(b)).
(B)	The state of transmitting-terminal power supply
For proper selection of operation mode of a modem,
it is necessary to check whether the transmitting terminal has a power source. Accordingly, we disconnected the lines and used an oscilloscope to measure
the voltage between L1 and L2 at the start point andend point. We found it was −50 V at the start point
and 0 V at the end point, which confirmed that thetransmitting terminal has a power source.
2.2.4 Cause of failure
Considering the above results, we concluded thatthe customer’s 50-bit/s leased line differs from thatstated in the information initially provided by thecustomer; the line uses a unidirectional 2-wire unipolar metallic-return system with a transmitting terminal having a power source. The VT2 or VT3 package
should be used for this system, and operation modes

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Vol. 21 No. 12 Dec. 2023

should be C1 for the start point and C2 for the end
point (Table 1).
2.2.5 Conclusion
On the basis of the above findings, communication
failure was resolved when C1 and C2 selected thesubscriber-line VT3 package. Since the metallic
transmission line could be replaced with an opticalcable, the metallic cable between the start-point andend-point COs could be eliminated.
3. Concluding remarks
This article introduced two failure cases in a 50-bit/s
leased line: modem communication failure at theearth-return circuit and the cause of failure to replacea metallic transmission line with an optical cable. It is
important to measure the waveform using an oscilloscope effectively to analyze 50-bit/s leased lines.
The Network Interface Engineering Group of TASC
provides technical support for early resolution ofproblems with equipment, terminals, and networks
by acquiring and analyzing data by using various
tools. We will continue to disseminate technologies
by providing technical support, developing tools, andholding technical seminars.

59External Awards
Young Scientist Presentation Award
Winner: Asuka Inoue, NTT Device Technology Laboratories
Date: September 19, 2023
Organization: The Japan Society of Applied Physics (JSAP)
For “Over 40 GHz Bandwidth Real-time Amplitude Measurementof 5 dB Squeezed Light by Optical Phase Sensitive Pre-amplification.”
Published as: A. Inoue, T. Kashiwazaki, T. Yamashima, N. Takanashi,
T. Kazama, K. Enbutsu, K. Watanabe, T. Umeki, M. Endo, andA. Furusawa, “Over 40 GHz Bandwidth Real-time Amplitude Measurement of 5 dB Squeezed Light by Optical Phase Sensitive Preamplification,” The 70th JSAP Spring Meeting, 16p-A405-6, Tokyo,
Japan, Mar. 2023.
Young Scientist Presentation Award
Winner: Ayumi Ikeda, NTT Device Technology Laboratories
Date: September 19, 2023
Organization: JSAP
For “Quantitative Analysis of Biological Species by Responsivehydrogel-based Dielectric Resonators.”
Published as: A. Ikeda, M. Nakamura, R. Takahashi, T. Tajima, and

NTT Technical Review

Vol. 21 No. 12 Dec. 2023

K. Hayashi, “Quantitative Analysis of Biological Species by Responsive-hydrogel-based Dielectric Resonators,” The 70th JSAP Spring
Meeting, 15a-B409-4, Tokyo, Japan, Mar. 2023.
Young Scientist Presentation Award
Winner: Riku Takahashi, NTT Basic Research Laboratories
Date: September 19, 2023
Organization: JSAP
For “Biomimetic Actuation Leveraging On-chip Buckling Deformation of Photoresponsive Gels.”
Published as: R. Takahashi, H. Miyazako, A. Tanaka, and M. Yamaguchi, “Biomimetic Actuation Leveraging On-chip Buckling Deformation of Photoresponsive Gels,” The 70th JSAP Spring Meeting,
17a-E102-8, Tokyo, Japan, Mar. 2023.
JSAP Fellow
Winner: Masaya Notomi, NTT Basic Research Laboratories
Date: September 19, 2023
Organization: JSAP
For exploration of novel properties of photonic crystals and application to integrated nanophotonics.

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