NTT Technical Review

September 2018 Vol. 16 No. 9
FeatureArticles:ResearchandDevelopment

Initiatives

forInternetofThings

Implementation

Research and Development to Create Value with IoTApplication for Rehabilitation Medicine Using Wearable Textile “hitoe”

Wireless Relay Technologies for Monitoring Underground Infrastructures



Data Stream Assist Technology Supporting IoT Services



Utilization of Edge Computing and IoT Sensors in Hierarchical Weather Forecasting System

Regular Articles


New Transport QoE-control Technology Enabling High-definition/High-presence Content
Distribution

Global Standardization Activities
Standardization of Automation Technology for Network Slice Management by ETSI Zero
Touch Network and Service Management Industry Specification Group (ZSM ISG)

Short ReportsCompletely Rewriting Industry’s Understanding of Transmitting High Quality Laser
Processing Light over Long Distances

External Awards/Papers Published in Technical Journals and Conference ProceedingsExternal Awards/Papers Published in Technical Journals and Conference Proceedings

Feature Articles: Research and Development Initiatives
for Internet of Things Implementation

Research and Development to Create
Value with IoT
Shuichi Yoshino and Hiroyuki Tanaka
Abstract

Utilization of Internet of Things (IoT) technology is advancing as part of efforts to create new value
in various fields, even those with little previous relation to information and communication technology.
In view of this IoT era that will drive industry and society forward, NTT has defined four necessary roles
in terms of requirements and technologies, and we are collaborating with our partners to build key technologies. In this article, we introduce technical development initiatives at the NTT laboratories to further
advance IoT.
Keywords: IoT, sensing, edge computing

1. Introduction
With the Internet of Things (IoT), all manner ofobjects in society are being connected to networks,
exchanging and processing information in cyberspace (the cloud), and producing value by visualizing
objects and occurrences in the real world or by providing feedback for control. It is much anticipatedthat the IoT will facilitate the creation of new industries in various fields and will be a means of resolving
issues faced by society as its use continues to spread.
At the NTT laboratories, we believe that a new era
has arrived, in which IoT is used to visualize, optimize, and control physical objects and movement insociety, and in this third-generation driving era, therole of information and communication networks isvery different from what it was earlier. Consequently,
we are conducting research and development (R&D)
to meet the different requirements and develop newusage domains [1].
A study by the Ministry of Internal Affairs andCommunications (MIC) of Japan [2] broadly categorized the use of IoT, based on collected data, into usesthat increase the value of products by providing
remote control, operation, or maintenance of robots
and machinery, and uses that improve processes incompanies and other organizations through visualization and optimization of business. An analysis
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Vol. 16 No. 9 Sept. 2018

revealed that as of 2015, IoT had been introduced into
20% of domestic products and services in a wide
range of fields including agriculture, energy, manufacturing, distribution, services, and data communications, and this is expected to rise to 40% by 2020.
2. Topics for further development and initiatives
in the NTT Group
However, the same study also reported many opinions indicating that scenarios for using products were
not clear or that the effectiveness was questionable.
Thus, to further develop IoT and expand the base ofusers in the future, it will be important to have environments and methods for creating value and realizing benefits, with low risk in terms of cost effectiveness, and allowing projects to start small and be verified easily. Thus, solutions to accelerate the spread of
IoT must both create value with IoT, and provide
methods for building IoT systems.
The NTT Group is working to create value with IoT
by collaborating with partners from the earliest stages
and building IoT technologies that realize value. For
example, in manufacturing we are working with
FANUC Corporation to develop an open platform
called the FIELD system*. This system uses edge
computing technology to collect and analyze the stateof operations in a factory in real time, to add
1Feature Articles

Agriculture

Smart cityZ
Y
X

Manufacturing

Shipping

Analytics &Prediction

Connected cars
Application
Middleware & library

Security

Data &
Software
Logistics

Management

Fast and distributed IoTprocessing platform
Software component
IoT data sharing
Security gateway
IoT gateway
Wired & wireless networks

Sense,
Connect &Drive

Security orchestration

Healthcare

Security for IoT devices
Sensors & devices

Fig. 1. Functional architecture.

efficiency and intelligence to manufacturing. By
enabling applications to be downloaded to the edges,
we are also working to realize evolving factories.
This service has been offered within Japan since
October 2017 [3].
To promote the use of IoT in the field of shipping,
we are working with the NYK Group to develop technologies for advanced management of maintenancethat take safety and the environment into consideration. This has included advanced vessel operations
and fault prediction for machinery [4].
We have investigated methods for building IoT systems and have created a functional architecture fortechnology to meet various IoT requirements. Thisarchitecture is being used as a reference for R&D.
The main functions as they relate to the real world areshown in Fig. 1.
The main functional elements of this architecture
are sensors & devices, with functionality to digitize
information from sensors and connect them to networks; IoT gateway, with functionality to convert to/from Internet protocols and connect to cyberspace;security gateway, which monitors the system in termsof communication flow and traffic behavior; IoT data
sharing, which enables data to be exchanged among
applications and devices with different specifications
and protocols; software component, which optimizes
data processing locations and software run-time environments; and middleware & library, which provides
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Vol. 16 No. 9 Sept. 2018

generic functionality to applications. A wide range ofapplications and services are expected with IoT, andnot all of them will need to use all of these technicalelements. The required functionalities can be combined and used with other technologies that may beon the market to suit particular applications.
The NTT laboratories are building these functions
on a base of open-source and other general-purpose
software to create systems that meet differing requirements in each field. We are ensuring that elements arehighly generalized and meet common requirements
to create a set of functional modules that can bereused. We continue to collaborate with partners in awide range of fields to quickly realize new value with
IoT, analyze and build universal functionality, andbuild environments in which these functions can beshared.
3. Directions for new technology and new value
We are developing technologies for each of the fourroles and technologies needed to implement IoT,
which are shown in Fig. 2. They are Sense, Connect& Drive, which digitizes data from things and is theinterface between real society and cyberspace; Data*

FIELD (FANUC Intelligent Edge Link and Drive) system is an
IoT system for manufacturers jointly developed by Cisco Systems, Rockwell Automation, Preferred Networks, and the NTT
Group under a concept defined by FANUC.

2

Feature Articles

Data &
Software
Logistics• Digitizing of data
• Connecting objects• Driving

Sense,
Connect& Drive• Data sharing and optimal
deployment of processing software

Analytics&
Prediction• Analysis• Preparation

Security• Maintaining safety

Fig. 2. Four roles and technologies in IoT.

& Software Logistics, which uses data and softwareand places them in the appropriate locations; Analytics & Prediction, which creates value from the data;
and Security, which enables processes in society to be
driven safely and securely using IoT.
3.1 K
 ey to Sense, Connect & Drive: simple operation
Users are often quite conscious of the cost of building and operating IoT systems, so such systems need
to be easy to build, maintain, and operate. It is important that sensors used to collect data can do so withsimple and easy procedures. The NTT Group is conducting R&D on “hitoe” to achieve biological data
sensors that can collect data simply by having theuser wear a garment, and is developing scenarios forusing it.
A recent example is a collaboration with Toray
Industries, Inc. and Fujita Health University to visualize the state of patient rehabilitation. The data collected will be used to provide higher quality rehabilitation in hospitals and other facilities in hopes ofresolving important issues in an aging society. Thiseffort is introduced in the article, “Application for
Rehabilitation Medicine Using Wearable Textile‘hitoe,’” in the Feature Articles in this issue [5].
As the use of IoT expands, expectations are also
increasing to use it in locations where networks thatprovide connectivity to cyberspace have not previously been available. For example, the NTT laboratories are conducting R&D on communication with
devices that can inspect underground infrastructure tomonitor deteriorating water pipes [6]. The goal in thisexample is to achieve highly reliable wireless comNTT Technical Review

Vol. 16 No. 9 Sept. 2018

munication from an underground water-pipe valve
box, where radio propagation losses are 50 dB or
more. Signal processing at the above-ground basestation is used, and low-power consumption formaintenance-free operation over several years isneeded. This effort is introduced in the article, “Wireless Relay Technologies for Monitoring Underground
Infrastructures,” [7] in this issue.
3.2 K eys to Data & Software Logistics: shareddata and structures, local data processing
There is much anticipation for new value createdusing big data with IoT, but according to an MIC
study, industry and government perceive that there
are issues with big-data utilization such as the cost ofdata collection and management and unclear costeffectiveness of data utilization [2]. Most IoT initiatives are currently advancing separately, but toexpand IoT more broadly in the future, standardization for data sharing will become more important,including standardization of data and common frameworks for handling it.
The NTT laboratories are conducting R&D andstandardization work on oneM2M as a potential
international standard for open data and use of data
across industries. Specifications for oneM2M werecreated as a platform, with a set of common functions
used in IoT systems.
Standards for interconnectivity with other existing
standards are also being created. Systems built withthe oneM2M architecture will be able to access collected data using the same application programming
interfaces (APIs), and different applications and users
will be able to use the same data more easily.
3Feature Articles

Applications in different fields can also access thedata using the same APIs, making it easier to linkwith and introduce knowledge from other fields,
which is important for the expansion of IoT.
The NTT laboratories are participating in R&D andstandardization for oneM2M and driving the creationof standard specifications and testing, toward completion of the specifications so they will become
widespread quickly [8].
Edge computing technology, which processes data
locally, is also promising as a way to create new value
with IoT. Compared with earlier information processing, mainly at either user terminals or in the cloud,edge computing is a technology that aims to create
new effects by placing data resources and performing
processing at points that are physically distributed
between them.
The NTT laboratories began R&D in this area early
and are testing ways to use this idea in various fields.
One such joint research initiative we have with theJapan Agency for Marine-Earth Science and Technology (JAMSTEC) is a hierarchical weather simulation
system that uses a hierarchical network structure.
This system is introduced in the article, “Utilizationof Edge Computing and IoT Sensors in Hierarchical
Weather Forecasting System,” [9] in this issue.
The continued development and expanding use of
IoT means that in addition to many simple IoT devices, high-performance devices such as high-resolution
cameras, with accompanying large volumes of data,
are beginning to appear. To provide networks that
support the use of such sophisticated and high-performance IoT devices, the NTT laboratories are conducting R&D on a data stream assist technology witha set of distributable functions that can achieve transmission for various data flow scenarios. This effort isintroduced in the article, “Data Stream Assist Technology Supporting IoT Services,” [10] in this issue.
3.3 K eys to Analytics, Prediction, Security: scalability and ease of use
The potential to create new value using big data
analysis and artificial intelligence technologies is
promising, but specialized knowledge and optimized
algorithms become more necessary as the amount ofdata handled increases. Security will also need to bestrengthened in order to deal with larger and moresophisticated attacks than ever before as IoT development advances. To expand IoT broadly and make it

NTT Technical Review

Vol. 16 No. 9 Sept. 2018available to everyone as a social infrastructure, it will
be important to build environments in which suchspecialized and complex processing can be used easily and efficiently.
4. Future prospects
Going forward, we will continue to conductadvanced R&D and to collaborate with partners invarious fields to create new value, further develop
IoT, and expand its use.
References[1]

R. Kawamura and S. Yoshino, “Research and Development Initiatives
on the Internet of Things at NTT,” NTT Technical Review, Vol. 15,
No. 9, 2017.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201709fa1.html[2] MIC, “White Paper on Information and Communications in Japan,”
http://www.soumu.go.jp/johotsusintokei/wp_eng.html[3] NTT press release issued on October 3, 2017 (in Japanese).
http://www.ntt.co.jp/news2017/1710/171003b.html[4] NTT press release issued on February 15, 2018.
http://www.ntt.co.jp/news2018/1802e/180215a.html[5] T. Ogasawara, K. Matsunaga, H. Ito, and M. Mukaino, “Application
for Rehabilitation Medicine Using Wearable Textile ‘hitoe,’” NTT
Technical Review, Vol. 16, No. 9, pp. 6–12, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201809fa2.html[6] S. Yoshino, “R&D on Technologies for Collecting, Transmitting, andProcessing Sensing Data of Civil Infrastructures (Underground Structures),” Booklet of the Cross-ministerial Strategic Innovation Promotion Program (SIP) Infrastructure Maintenance, Renovation andManagement, pp. 88–89, 2017.
https://www.jst.go.jp/sip/dl/k07/booklet_2017_A4_en.pdf[7] Y. Fujino, H. Fukumoto, H. Katsuda, and K. Akabane, “Wireless
Relay Technologies for Monitoring Underground Infrastructures,”
NTT Technical Review, Vol. 16, No. 9, pp. 13–18, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201809fa3.html[8] K. Harada, H. Maeomichi, and I. Yamasaki, “Standardization Trendsof oneM2M for Horizontal Internet of Things Platform,” NTT Technical Review, Vol. 16, No. 4, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201804gls.html[9] R. Nakada, K. Mori, and N. Takahashi, “Utilization of Edge Computing and IoT Sensors in Hierarchical Weather Forecasting System,”
NTT Technical Review, Vol. 16, No. 9, pp. 28–32, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201809fa5.html[10] N. Higo, T. Tsubaki, K. Koshiji, T. Tsubaki, and T. Kuwahara, “DataStream Assist Technology Supporting IoT Services,” NTT Technical
Review, Vol. 16, No. 9, pp. 19–27, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201809fa4.html

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

4

Feature Articles

Shuichi Yoshino

Executive Research Engineer, Senior Manager,
Wireless Systems Innovation Laboratory, NTT
Network Innovation Laboratories.
He received a B.E. and M.E. in mechanicalengineering from Kanazawa University in 1990
and 1992. He joined NTT in 1992 and worked on
the development of a satellite Internet system andwireless networking technology. He is currently
engaged in R&D of wireless technology for IoT
and mobile access.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

Hiroyuki Tanaka

Senior Research Engineer, Senior Manager,
Ubiquitous Service Systems Laboratory, NTT
Network Innovation Laboratories.
He received a B.E. from Kyushu University,
Fukuoka, in 1993 and an M.E. from Nara Institute of Science and Technology in 1995. He
joined NTT in 1995. His current interests include
design and implementation of future computing
systems.

5

Feature Articles: Research and Development Initiatives
for Internet of Things Implementation

Application for Rehabilitation
Medicine Using Wearable Textile“hitoe”
Takayuki Ogasawara, Kenichi Matsunaga, Hiroki Ito,and Masahiko Mukaino
AbstractNTT, Toray Industries, Inc., Fujita Health University, and NTT DOCOMO have begun trials on patient
rehabilitation support using the functional material called “hitoe,” which can take continuous measurements of biological data simply by having patients wear it. As innovation progresses in medical andnursing care, it is necessary to improve the quality of rehabilitation, especially for elderly patients, in therecovery progress and return to daily life, and in preventing the recurrence of debilitation. This article
introduces new initiatives to develop wearable technology in light of these social issues.
Keywords: wearables, rehabilitation, medicine, smart clothing

1. Rehabilitation during convalescence
Systems for providing medical and nursing careservices are being reformed by the government inJapan [1, 2]. As part of this effort, there has been astrategy to reduce the number of hospital beds where
advanced, acute medical care has been provided till
now and to increase the number of beds that can more
fully meet regional medical care needs (Fig. 1). Rehabilitation during convalescence plays an importantrole in these reforms. Patients who engage in focusedrehabilitation after receiving acute medical treatment,
when their condition first begins to stabilize, canaccelerate the recovery of function and improve theiractivity in daily life. Such rehabilitation can also help
prevent patients from becoming bedridden, returnthem to family and society, and limit recurrences ofdebilitation. Providing high-quality rehabilitation istherefore an important social issue in an aging society, going beyond the scope of private enterprise. As
such, NTT, Toray Industries, Inc., Fujita Health University, and NTT DOCOMO began practical testing
to improve the quality of rehabilitation services using“hitoe” wearable technology in February 2017 [3].
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Vol. 16 No. 9 Sept. 2018

2. Smart clothing and “hitoe”
functional material
NTT and Toray developed “hitoe,” which is a functional material that can take continuous measurements of biological information when a person wears
it [4]. The material is created by coating the surfaceof fibers with a conductive polymer (PEDOT-PSS:
poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)), resulting in a very flexible, hydrophilic, anddurable material that is also electrically conductive[5]. Smart clothing incorporating this material can beused to measure changes in heart rate over long periods of time in a range of scenarios. It can also be
combined with other sensors such as accelerometers,
and new, higher-order feature values can be computed
to expand the range of possible applications in various
ways [6–8] (Fig. 2). This article describes an example
of an application in the area of rehabilitation.
3. Clinical research with rehabilitation patients
The medical effects of rehabilitation can be broadlyclassified into general effects, in which exercise
6Feature Articles

Status in 20122025 outlook

Many beds for advanced
acute medical care

Increase in beds meeting regional needs(including recovery after acute care).
To provide efficient, high-quality
medical careFig. 1. Innovation in medical care system.

Developing diverse applications
Secondary features(computed)

Drowsiness

Exerciseintensity
Primary features(measured)ElectroHeart rate
cardiogram

FatigueElectromyogram

Sleep
stagesBody
mobility

Acceleration

Amountof activity

Gait
PostureFig. 2. Expanding applications of “hitoe.”affects the entire body, and specific effects, which
contribute to addressing particular motions or functions in the patient’s life. For general effects, the goal
is to affect the whole body by ensuring that a safe andappropriate amount of exercise is achieved in thedaily routine in the rehabilitation environment, butthere have not been strong, clinical, and measurable
indices for this. However, heart rate and activity data
can be collected easily using “hitoe” 24 hours a day,and not just during the limited rehabilitation training
period with therapists.
An overview of the system is shown in Fig. 3.
Patients needing rehabilitation wear smart clothing
incorporating “hitoe.” Biological data measured fromthe patient by the clothing are sent to a server througha smartphone or a relay device (an Internet of things(IoT) gateway) in the hospital and can be examinedusing a viewer. Doctors can use the collected data toevaluate the suitability of the activity in the treatment
NTT Technical Review

Vol. 16 No. 9 Sept. 2018environment and can evaluate the general effects. The
system also gives an understanding of patient lifestyle patterns, so it can help in giving safe and highquality guidance and managing everyday risks moreeasily. It could also be useful for developing morecomprehensive rehabilitation treatment systems. The
components of the system are described below.
3.1 Smartphones
Most wearable devices on the market strive to
reduce energy consumption by using simple displayswith light emitting diodes and low-energy wirelesscommunication such as Bluetooth so they can operateover long periods of time. Smartphones can be used
to maximize the value of such devices. They can convey real-time feedback to patients on a high-quality
display and send data to servers on the network using
LTE (Long-Term Evolution) or Wi-Fi. Extensibility
using applets is also a major benefit. NTT is studying
7

Feature Articles

Fast and distributed IoT processing platform- Displaying results- Exporting reports

Data collection,
management, reference
Network

Viewer
Relay devices
Doctor

Providing feedback to patient

Smartphone

Provide high-quality evidence based medicine.

Transmitter

IoT gateway“hitoe” wear forrehabilitation

Therapist
Support the patient with suitable intervention.

Capture electrocardiogram,acceleration data.

Nurse
Provide communicative care and monitoring during
the night.

Rehabilitation
room etc.

Hospital room

IoT: Internet of Things

Fig. 3. Rehabilitation support system using “hitoe.”

new ways to provide rehabilitation support using
smartphones to increase patient motivation andactively encourage exercise.
3.2 IoT gateway
IoT gateways are installed in buildings and otherenvironments. They enable free measurement of sensor data without patients having to hold their smartphones, and they transmit the collected data throughthe network to a storage device. The NTT laboratories developed an IoT gateway using compact, offthe-shelf hardware and our own time synchronizationand protocol control software [9] (Fig. 4).
The time synchronization technology provides
accurately synchronized timestamp data on the IoT
gateway by estimating the time using the Network
Time Protocol and correcting for effects includingtransmission delay on the wireless segments andpacket retransmission times when bandwidth is congested, so that times can be recorded accurately fordata from sensors that do not maintain time information.
The protocol control technology enables data transmission independent of the type of sensor by converting among transmission protocols with different
communication standards and sensor data formats. In
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Vol. 16 No. 9 Sept. 2018

the future, these technologies will enable data collection and analysis to be coordinated among a wide
range of sensors in addition to “hitoe” with video,
location, and other data.
In these experiments, approximately 50 IoT gateways were installed in patient wards in hospitals—inrooms, corridors, rehabilitation facilities, and otherareas—to maintain stress-free 24-hour data collection. The amount and frequency of data sent to theserver was controlled by processing data signals collected on IoT gateways, which enabled collection of
sensor data from approximately 100 patients.
3.3 Data collection, aggregation, referencing
The system handles data storage, aggregation, andreferencing on the server. The server part of the system consists of two functions: one to store the biological data gathered from “hitoe” via the smartphones and IoT gateways, and another to process,aggregate, and display the stored biological data.
Using both smartphones and IoT gateways to gather
data enables the data to be collected continuously andwith flexibility, no matter where the patients are. This
is not only within the hospital but can include homecare after leaving the hospital.
Commercial applications linked with “hitoe” for8Feature Articles

Common wireless hardware
Standard-dependent
component

IoT gateway
Commoncomponents

Timing control to avoid
collision

Packetgenerator
Wi-Fi support

NTP
back-end
processor

RTC-IC

Bluetooth support

Protocolconverter

Data-savememory

Wi-Fi
MAC

PHY

Bluetooth
MAC

Zigbee support

ZigbeeSupport for new
standards

MAC

PHY

Masteror
gatewayPHY

New standards
MAC- Extracts needed parts- Protocol compatibility
Supports addition of wireless standards

PHY

Possible to add new wireless standards

MAC: media access control
NTP: Network Time Protocol
PHY: physical layer
RTC-IC: real-time communications integrated circuit

Fig. 4. IoT gateway architecture.

collecting biological data have already been developed, and customer needs can be met using a fast anddistributed IoT processing platform [3] that is easy toscale out when the volume of data increases. For our
experiments, we implemented an application using
the fast and distributed IoT processing platform, withfunctionality to aggregate and display the collected
data. Aggregating and displaying the data enables thedata to be used for medical research and makes it possible to provide practical feedback to patients in theactual rehabilitation environment.
To ensure that the biological data collected on the
IoT processing platform are suitable for applications
in medical research, the system maintains relatively
frequently sampled data. For this reason it can be difficult, for example, for a doctor to give feedback to apatient using a real-time graph of trends over longer
periods of time. Therefore, for these experiments, we
also prepared an application to aggregate and display
results, compensating for such difficulties. The
aggregation function aggregates biological datastored on the fast and distributed IoT processing platform over set periods of time, calculates statistics
such as overall heart rate and total calorie consumptions, and stores the results in a database. The display
function then provides access to the biological andstatistical data from personal computers connected to
NTT Technical Review

Vol. 16 No. 9 Sept. 2018the hospital network using a web-based user interface(Fig. 5). In addition to providing access to the biological data, the web-based user interface supports
entry of comments and downloading of detailed databy doctors.
This system also supports measurement and monitoring of a physiological cost index, which is a typicalphysiological indicator of performance while walking that is used for patients in physiotherapy. It can beused together with long-term patient monitoring to
improve the quality of daily rehabilitation guidancefrom doctors and therapists and to support the use ofdata for academic activities.
3.4 Features
The heart rate and state of activity are extracted
from sensor data as features for visualizing patient
condition. The patient’s state of activity can be categorized as lying down, standing/sitting upright, or
walking based on computations from data acquired
from a three-axis accelerometer in the transmitter
attached to the garment (Fig. 6). The length of timethat patients stayed upright and the number of steps
walked are objective indicators to evaluate thepatient’s condition. An elevation of the heart rate
indicates a physiological burden, and this will be used
as a personal or subjective indicator.
9

Feature Articles

Patient
profileResults ofthe day

Results ofthe period

Back to patients list

PCI

Results on 19 Dec. 201720 Dec. 2017 19:10
Real-time conditions

Heart rate while walking

Heart rate while sitting or standing

Heart rate while lying down

Maximum heart rate

Total heartbeats/day

Summary for 24 hours

Lying
down

Last update 19:00

Walking

Unit:
hour

6h
12 h

December
Su. Mo. Tu. We. Th. Fr. Sa.

6h
Sitting orStanding

Lying
down

PCI: physiological cost index

Fig. 5. Example of web user interface.

Acceleration
sensorTransmitter

Nonactive

ActiveLying down

Still

Highly reliable/stable posture
estimation based on real patientmeasurements

Staying upright

Walking detection

Sitting or
standing

Walking
WalkingLight activity

High-performance walking
detection supporting
hemiparesis

Strong activity

Fig. 6. Activity state estimation using acceleration data.

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Vol. 16 No. 9 Sept. 201810

Feature Articles

Non-active patient

Activity stateHeart rate (bpm)

Active patient

Lying
down

Sitting or
standing

Lying
down

Walking

Sitting or
standing

Walking• Quantify physical load or intensity of activity.
• Track process of recovery.
Able to understand information important for rehabilitation in a real environment

Fig. 7. Example of actual results.

These feature extractions were achieved by using ahighly reliable algorithm based on real experimental
measurements from various patients. By correlatingthese types of features, we can obtain detailed information that is important for rehabilitation in realenvironments, for example, the length of time patientsare able to stay upright due to recovery of functionality, and the intensity of exercise patients can tolerate
as time passes after their conditions occur. This sortof information is expected to help in improving thequality and efficiency of rehabilitation.
4. Experimental results
In one experiment conducted with this system,measurements were taken for two stroke inpatientswith hemiparesis. The results are shown in Fig. 7.
One of the subjects needed assistance for most daily
activities, while the other did not. The differences
between the two are clear in the measurement results.
The subject not needing assistance was much more
active, and there was a strong tendency toward having
a higher heart rate while active.
This difference is understandable if we surmise thatthe subject not needing assistance can use his/herbody more easily, making it easier to return to active
daily life. However, the system can do more thancompare cases of needing or not needing assistance.
For cases involving patients who need assistance,
when we compare those who are active during hospitalization and those who are more cautious with theiractivity, it is important to focus on which of thesetends to have a better recovery, and why. This is
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Vol. 16 No. 9 Sept. 2018

because it could suggest that the general effects we
discussed earlier are an important mechanism.
The system also shows the patient’s physical condition, so interventions can be optimized for individual
patients, and it can provide clues as to the cause if
there is a change in condition. We have already conducted measurements with more than 70 patients andhave encountered some very interesting cases. We are
accumulating studies with this sort of evidence andparticipating in discussions at medical conferences,and through these activities we hope to develop
monitoring methods to improve the quality of rehabilitation.
5. Future prospects
These efforts are aimed at developing systems thatprovide high-value services to patients and medical
treatment providers by proposing monitoring methods using wearable technology and providing medical evidence. In addition to contributing to the development of rehabilitation, we will go beyond rehabilitation in the future, advancing development to reducethe burden on patients and medical providers, including areas such as remote rehabilitation and home
support.
References[1]

Agenda of the 208th General Meeting of Central Social Insurance
Medical Council, Ministry of Health, Labour and Welfare of Japan,
2011 (in Japanese).
http://www.mhlw.go.jp/stf/shingi/2r9852000001vpkq-att/
2r9852000001vpok.pdf

11Feature Articles

[2]

[3]

[4]

[5]

[6]

S. Nakamura, “Future of Reginal Medical Services (1)—Medical andNursing Care Services in 2025,” NHK News Commentators Bureau,”
2018 (in Japanese).
http://www.nhk.or.jp/kaisetsu-blog/400/292094.html
T. Kondo, Y. Yamato, M. Nakayama, A. Chiba, K. Sakaguchi, T.
Nishiguchi, T. Masuda, and T. Yoshida, “Natural Sensing with ‘hitoe’
Functional Material and Initiatives towards Its Applications,” NTT
Technical Review, Vol. 15, No. 9, 2017.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201709fa3.html
S. Tsukada, N. Kasai, R. Kawano, K. Takagahara, K. Fujii, and K.
Sumitomo, “Electrocardiogram Monitoring Simply by Wearing a
Shirt––For Medical, Healthcare, Sports, and Entertainment,” NTT
Technical Review, Vol. 12, No. 4, 2014.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201404fa4.html
K. Takagahara, K. Ono, N. Oda, and T. Teshigawara, “‘hitoe’—A
Wearable Sensor Developed through Cross-industrial Collaboration,”
NTT Technical Review, Vol. 12. No. 9, 2014.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201409ra1.html
N. Kasai, T. Ogasawara, H. Nakashima, and S. Tsukada, “Development of Functional Textile “hitoe”: Wearable Electrodes for Monitor-

Takayuki Ogasawara

Research Engineer, Wearable Appliances
Development Project, NTT Device Innovation
Center.
He received a B.E. and M.E. in applied physics
from Hokkaido University in 2006 and 2009. He
also completed the Developmental Brain Science
Master’s Program at the Research and Education
Center for Brain Science, Hokkaido University,
in 2009. He joined NTT Microsystem Integration
Laboratories in 2009. His current interests
include biosensors and wireless communications. He received the 2018 Best Magazine Paper
Award of the Institute of Electronics, Information, and Communication Engineers (IEICE)
Communications Society. He is a member ofIEEE (Institute of Electrical and Electronics
Engineers) and IEICE.

Kenichi Matsunaga

Research Engineer, Wearable Appliances
Development Project, NTT Device Innovation
Center.
He received an M.E. in electronics from Tokyo
Institute of Technology in 2010. He joined NTT
Microsystem Integration Laboratories in 2010and studied low power complementary metaloxide semiconductor (CMOS) circuit design for
wireless sensor nodes. He moved to NTT Device
Innovation Center in 2015, where he has beendeveloping IoT devices. His research interests
include CMOS circuits and sensor networks. He
is a member of IEICE and the Japan Society ofApplied Physics.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

[7]

[8]

[9]

ing Human Vital Signals,” B-plus: IEICE Communications Society
Magazine, Vol. 41, pp. 17–23, 2017.
T. Ogasawara, K. Ono, N. Matsuura, M. Yamaguchi, J. Watanabe, and
S. Tsukada, “Development of Applications for a Wearable Electrode
Embedded in Inner Shirt,” NTT Technical Review, Vol. 13. No. 1,
2015.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201501fa2.html
A. Chiba, K. Tsunoda, H. Chigira, T. Ura, O. Mizuno, and T. Tanaka,“Estimating Critical Fusion Frequency from Heart Rate Variability,”
The 37th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBC 2015), Milan, Italy, Aug.
2015.
“Expanding the Use of ‘hitoe’ and Development of Fundamental
Technology for Data Collection,” Business Communication, Vol. 54,
No. 7, pp. 10–12, 2017 (in Japanese).
http://www.ntt.co.jp/dic/theme/pdf/2017/bizcom/bizcom17-7-4.pdf

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

Hiroki Ito

Research Engineer, Cloud System SE Project,
NTT Software Innovation Center.
He received a B.E. in mechanical engineeringand an M.E. in biomedical engineering fromTohoku University, Miyagi, in 2013 and 2015.
He joined NTT in 2015, where he is involved inresearch and development of a cloud computing
platform. He is currently researching and developing an edge computing platform for IoT systems.

Masahiko Mukaino

Physiatrist, Senior Assistant Professor of
Department of Rehabilitation Medicine at Fujita
Health University.
He received an M.D. Diploma and Licensefrom Kyushu University School of Medicine,
Fukuoka, and a Ph.D. from Keio University
School of Medicine, Tokyo. His current researchinterests include activity monitoring, motion
analysis, and rehabilitation robotics. He is amember of the Japanese Society of Rehabilitation Medicine, the Japanese Society of Clinical
Neurophysiology, the Japan Neuroscience Society, and the Society for Neuroscience.

12

Feature Articles: Research and Development Initiatives
for Internet of Things Implementation

Wireless Relay Technologies for
Monitoring Underground
Infrastructures
Yosuke Fujino, Hiroyuki Fukumoto, Hajime Katsuda,
and Kazunori Akabane
Abstract

With the progress made in Internet of Things (IoT) technology, expectations have been raised for IoT
services in areas outside the bounds of network coverage such as underground, underwater, and sky
environments. We have been developing wireless communications systems aimed at achieving monitoring capabilities of aging underground infrastructures. Our systems make use of wireless relay terminals
installed on vehicles or utility poles to efficiently collect data from sensors installed in undergroundinfrastructures. In this article, we introduce two recently developed technologies for radio relay systems
that are designed to reduce the costs of installation and operation of the system. One extends the coveragearea, and the other reduces power consumption.
Keywords: underground infrastructures, radio relay system, transmitter diversity

1. Introduction
The growth of the Internet of Things (IoT) has been
progressing rapidly, and expectations have beenraised for IoT services to be provided in areas outside
the bounds of network coverage. These include environments underground, under water, and in the sky.
Monitoring of aging underground infrastructures
such as water pipes is one potential use case. Most
water pipes in Japan laid in the era of high economic
growth are aging rapidly, and the proportion of deteriorated water pipes is expected to exceed 40% in2020 [1].
Investigations of water leakage from water pipes aswell as maintenance of these pipes currently require
skilled engineers, who conduct inspections manually.
However, such inspections relying on skilled personnel will become harder to carry out in the future
because of a manpower shortage due to the declining
birthrate and the aging population. Therefore, theinspection of underground infrastructure making use
of IoT combined with various kinds of sensors and
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Vol. 16 No. 9 Sept. 2018

wireless communications technologies have beenstrongly expected for efficient operations.
2. Wireless relay systems for monitoring
underground infrastructures
An underground environment such as a water pipe
is an enclosed space where the radio propagation pathis extremely limited. Thus, radio waves do not travel
very far even when compared with indoor environments such as inside buildings. Penetration loss fromoutdoors to indoors is known to be about 10–30 dB at
frequency bands around 1 GHz, which are frequently
used in IoT systems [2].
In contrast, the penetration loss from the ground tothe valve box of water pipes installed underground isabout 50 dB [3]. Hence, it is difficult to accommodate
all sensors installed underground by using 4G(fourth-generation wireless systems) and LTE (LongTerm Evolution), which is assumed to be used in
outdoor and indoor environments.
Therefore, we have been developing novel radio13Feature Articles

Wide area network(LTE, LoRaWAN etc.)
Fixed AP
Static method
Monitoring
serverCoverageup to 200 m

MobileAP

Underground infrastructure(water supply pipe)

Wireless transfer(920-MHz band)

Drive-by method

Valve box

Transceiver(920 MHz, LF)
Data processing
Battery
SensorSensor terminal

AP: access point
LF: low frequency
LoRaWAN: Long Range wide area network, developed by the LoRa Alliance.

Fig. 1. Concept of wireless relay system for monitoring underground infrastructure.

relay systems that efficiently collect data from sensors
under ground-level structures by using relay stations
installed on cars and on utility poles [4]. A schematic
drawing of our proposed system is shown in Fig. 1. Inradio relay systems, efficient installation and operation of repeaters is important. Hence, we have developed two techniques to achieve this. One techniqueextends the coverage area of the relay system, whichenables the repeaters to accommodate a large numberof sensors over a wide area. Consequently, we canreduce the number of relay units installed. The othertechnique saves power. It enables relay terminals to
operate on batteries, which makes it possible to installthem anywhere, even in locations without a power
supply.
3. Technique for extending coverage area
In wireless communications, the strength of radio
waves gradually weakens as the communication distance increases. There are two simple methods toextend coverage areas. One is to improve receiversensitivity by sacrificing transmission speed. In
recently introduced wide area communication systems such as LoRa [5] and Sigfox [6], an ultrahighsensitivity of –130 dBm or more has been achieved
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

by limiting the speed by up to several hundred bits per
second. However, since the required air time, or therunning time of a transceiver, becomes longer as thetransmission speed becomes slower, the power consumption increases.
The other method is to increase the transmission
power. However, this also leads to an increase inpower consumption at the transmitter. Therefore,
other technologies for extending coverage areas arenecessary for battery-powered long-life communication systems such as monitoring systems for underground infrastructures.
We are working to extend the coverage area by
focusing on a phenomenon referred to as multi-pathfading, which has a peculiar effect on radio communications. Radio waves in general propagate throughmultiple paths due to diffraction and reflection.
Hence, the received signal is the sum of multiple
waves, each of which traveled along a different path.
With multi-path fading, the reception power levelvaries drastically depending on the receiving position
due to differences in the phase relationship between
each path (Fig. 2(a)). For example, at receiving positions where two waves with the same phase are combined, the strength of the received signal is 3 dB
higher than the signal of a single path. On the other14

Feature Articles

In-phase
RX signal
RX
level

Periodically repeat
in-phase and reverse phase.

Reverse phase
RX signal

Success

RX signal
RX
level

Noise

FailureRX signal

Time

Noise

RX
level

RX signal

Similar to
moving terminal

Success
Noise

RX signal
Time

Time

Extendcoverage(a) Conventional(b) Proposed

RX: receiverFig. 2. Technology to extend coverage.

hand, the strength of the received signal significantly
weakens at positions where two waves with reverse
phase, or a 180-degree difference from one another,
are combined. To cope with such fluctuations instrength, wireless communications systems are generally designed with a level margin according to therequired quality.
Multi-path fading can cause a level fluctuation at acycle of one wavelength or less. For instance, in a
1-GHz frequency band, it occurs at a cycle of 15 cm
or less. In mobile communication systems whereusers typically use cell phones holding them in theirhand, the terminal moves around naturally by about
several centimeters. Moreover, it is possible for a
person to autonomously move the terminal when it is
not connected with a base station. Therefore, the linklevel margin that takes into account the effect ofmulti-path fading can be reduced more than in othercommunication systems.
In contrast, when the terminal is installed in a fixed
position and does not autonomously move, as in asensing system for underground infrastructures, alarge level margin is required since the phase relationship of arrival waves is unchanged. This margin isa factor that limits the communication distance for
IoT wireless systems.
To address this problem, we have developed a techNTT Technical Review

Vol. 16 No. 9 Sept. 2018

nology that suppresses the fluctuation of the reception level by transmitting radio waves from multiple
antennas simultaneously with slightly different frequencies [7]. This makes it possible to forciblychange the phase relationship of arrival waves at the
fixed reception point. This is analogous to generatinga slight movement of the terminal. As a result, thearrival waves are not combined in reverse phases.
Hence, the required level margin can be reduced, andthe coverage area can be extended, as shown in
Fig. 2(b). Although the reception level fluctuates
greatly within a packet by applying this technique,such distortion can be recovered by a receiver
equipped with compensation functions for movement
if an appropriate frequency offset is set.
This technology can be applied to various wirelesssystems. As an example, we experimentally evaluatedthe effectiveness of this technology when applied to a
LoRa system. The relationship between Eb/No (signal energy versus noise power density ratio per bit)and packet error rate (PER) under the multi-path fading environment is shown in Fig. 3. The graph showsthat the proposed method reduces the required Eb/No
at the 1% point of PER by about 5 dB compared to theconventional method. This means that the level margin can be reduced by about 5 dB when designinga coverage area with a 1% dead zone (the ratio of15

Feature Articles

100

Packet error rate (%)

wo fading (AWGN)
w fading (Proposed)
w fading (Conventional)
10

Required margin for proposed method
1

Improvement (about 5 dB)

Required margin for conventional method

0.1

0

5

10

15

Energy per bit-to-noise power ratio (dB)
AWGN: additive white Gaussian noise

Fig. 3. Performance of packet error rate.

terminals that cannot communicate) allowed. In
non-line-of-sight communications, the signal strength
is mostly inversely proportional to the third power ofthe distance. Hence, the proposed method can extend
the reachable distance by about 1.5 times longer thanthe conventional method by reducing the level marginof 5 dB.
4. Technology for reducing power consumption
IoT radio devices have achieved a battery life ofseveral years by saving power consumption using thesleep state. However, power saving using sleep
modes cannot easily be applied with relay stations
since they are always waiting for data to arrive fromsensor terminals and must remain in a receive mode.
Therefore, another means of reducing power consumption is necessary to extend the battery life ofrelay terminals.
A method referred to as preamble sampling has
been proposed to achieve a way for receivers to waitfor data reception with low power consumption [8].
In preamble sampling, the receiver performs preamble detection at regular intervals as it waits for thearrival of data. Meanwhile, before the transmitter
sends data, it transmits preambles with longer lengths
than the period of receiver detection intervals. This
makes it possible for the receiver to receive signals
without fail, as shown in Fig. 4(a). With preamble
detection, reliable signal detection can be achieved in
NTT Technical Review

Vol. 16 No. 9 Sept. 2018a short time even in environments where large environmental noise exists, or when the noise power isgreater than the signal power. CSL (coordinatedsampled listening), which is a kind of preamble sampling, is adopted as the power saving technology inIEEE* 802.15.4e.
However, in an unlicensed band shared by various
wireless systems, it is impossible to send a long preamble with a length that is longer than a certain
length because the air time of a radio signal at one
time is limited by the radio laws of each country. For
example, in Japan’s 920-MHz band, the continuoustransmission time at one instance is limited to 400 ms(4 s). For this reason, an intermittent standby withintervals longer than a certain length cannot be
achieved. Hence, reducing the power consumption of
repeaters is difficult.
To address this issue, we have developed a technique to activate a relay terminal using multiple transmission of divided preambles. This involves appropriately controlling the transmission length and thetransmission interval of divided preambles, making it
possible to reliably activate the relay terminals withthe shortest time and minimum power while waiting
for the arrival of data at an arbitrary reception interval, as shown in Fig. 4(b). The method enables relay
terminals to set a long intermittent reception intervalthat does not depend on the continuous transmission*

IEEE: Institute of Electrical and Electronics Engineers

16Feature Articles

4 s or lessin 920-MHz band4 s or lessin 920-MHz band

TX

TX

RX

RX
(a) Conventional(b) Proposed

Received signals

Preamble detection

Preamble transmission

Response signal transmission

Data transmission

TX: transmitter

Fig. 4. Power saving standby operations.

Battery life (years)

15

10

osed

Prop
5
Conventional*

0
0

2

4

6

8

10

Intermittent reception interval (s)* when length of data is 2 sFig. 5. Performance of power saving technology.

time that is restricted by radio laws. Hence, therepeater can be driven by the battery for several years.
As an example, we conducted an experiment toevaluate the effectiveness of our proposed method for
wireless systems using Japan’s 920-MHz band. The
relationship between an intermittent reception interval and battery life is shown in Fig. 5. In the experiment, the battery capacity was 3000 mAh, the current
consumption for data transmission and measurement
was 0.5 mAh per day, and the current consumption at
reception was 20 mA. The period of intermittent
reception time was 10 ms. This technique enables
repeaters to set a long intermittent reception interval
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

regardless of the transmission time limit. Moreover, abattery life of five years or more can be achieved by
setting the intermittent reception interval to 5 s ormore.
5. Future work
We will continue to carry out research and development while working in cooperation with water
enterprises and leakage research organizations to further advance the technology described here. In addition, because the extension technology and powersaving technology introduced in this article are17

Feature Articles

general-purpose technologies independent of theradio system, we plan to promote horizontal deployment to various uses other than underground infrastructure monitoring.

[4]

Acknowledgment
Part of this work was supported by the Council for
Science, Technology and Innovation project called“Cross-ministerial Strategic Innovation Promotion
Program (SIP), Infrastructure Maintenance, Renovation, and Management” (Funding agency: JST).
References
[1]
[2]
[3]

Japan Water Works Association, “Water Statistics,” No. 97, 2014.
Recommendation ITU-R P.2109-0: “Prediction of Building Entry
Loss,” 2017.
S. Teruhi, Y. Yamaguchi, and J. Akahani, “Water Leakage Detection

Yosuke Fujino

Research Engineer, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received a B.E. and M.E. in electrical andelectronic engineering from Shizuoka University
in 2002 and 2004. He joined NTT Network Innovation Laboratories in 2004 and engaged inresearch on multi-user detection for a multiantenna, multi-user wireless system. He is currently researching a low-latency and low-power
media access control (MAC) protocol and transmitter diversity for IoT wireless systems. He is amember of the Institute of Electronics, Information and Communication Engineers (IEICE).

Hiroyuki FukumotoResearcher, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received a B.E. in engineering from Kobe
University in 2013, and an M.E. in informatics
from Kyoto University in 2015. He has been withNTT Network Innovation Laboratories since2015. His research interests include digital signal
processing and information theory in communication systems. He received the Best Paper
Award from IEICE SmartCom 2016 and the Best
Paper Award and Special Technical Award in
Smart Radio from IEICE Smart Radio in 2017.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

[5]
[6]
[7]

[8]

System for Underground Pipes by Using Wireless Sensors andMachine Learning,” Journal of Disaster Research, Vol. 12, No. 3, pp.
557–568, 2017.
S. Yoshino, “R&D on Technologies for Collecting, Transmitting, andProcessing Sensing Data of Civil Infrastructures (Underground Structures),” Booklet of the Cross-ministerial Strategic Innovation Promotion Program (SIP) Infrastructure Maintenance, Renovation andManagement, pp. 88–89, 2017.
https://www.jst.go.jp/sip/dl/k07/booklet_2017_A4_en.pdf
LoRa Alliance, https://www.lora-alliance.org/
Website of Sigfox, https://www.sigfox.com/
Y. Fujino, S. Kuwano, S. Ohmori, T. Fujita, and S. Yoshino, “CellRange Extension Techniques for Wide-area Ubiquitous Network,”
Proc. of the 10th International Symposium on Autonomous Decentralized Systems (ISADS 2011), Kobe, Japan, June 2011.
A. El-Hoiydi, “Aloha with Preamble Sampling for Sporadic Traffic in
Ad Hoc Wireless Sensor Networks,” Proc. of the 2002 IEEE International Conference on Communications (ICC 2002), New York, USA,
Apr. 2002.

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

Hajime Katsuda

Researcher, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received a B.E. and M.E. from Tohoku
University, Miyagi, in 2011 and 2013. Since joining NTT Network Innovation Laboratories in
2013, he has been engaged in research and development (R&D) of wireless technology for IoT
wireless access systems. He received the Young
Researcher’s Award from IEICE in 2016. He is amember of IEICE.

Kazunori Akabane

Senior Research Engineer, Supervisor, Wireless Systems Innovation Laboratory, NTT Network Innovation Laboratories.
He received a B.E. and M.E. from Keio University, Kanagawa, in 1994 and 1996. He joined
NTT Wireless Systems Laboratories in 1996,
where he has been involved in the R&D of wireless personal communication systems and software-defined radio systems. He is currently
engaged in R&D of IoT/M2M (machine-tomachine) wireless access systems.

18

Feature Articles: Research and Development Initiatives
for Internet of Things Implementation

Data Stream Assist Technology
Supporting IoT Services
Naoki Higo, Takuma Tsubaki, Kohjun Koshiji,
Toshimitsu Tsubaki, and Takeshi Kuwahara
Abstract

NTT Network Technology Laboratories has been researching and developing data stream assist technology that can be deployed lightly and flexibly to provide a network that supports complex services
using Internet of Things (IoT) devices with high functionality and performance. In this article, we introduce technologies that improve the utilization efficiency of the network and the convenience of IoT
services by changing the communication protocol, communication timing, and traffic volume according
to various multipurpose versions of 4K surveillance camera images.
Keywords: edge computing, IoT services, video surveillance

1. Introduction
Research and development (R&D) of the Internetof Things (IoT) has been accelerating in recent years,
and it is becoming more and more common for various devices with communication modules to be connected to a communication network. With the expansion and progress of IoT, progress is being made intechniques that enable visualization of the surrounding environment such as the movement of workers ina warehouse, and remote operation and automation ofwork tasks, and this progress is expected to improve
productivity.
Relatively simple devices such as temperature sensors and power switches are used in many IoT services that are now being provided, but other devices
such as monitoring cameras, drones, robots, and VR(virtual reality) equipment with high functionality
and performance are also included in the concept of
IoT. Such high-functionality and high-performancedevices can transmit and receive raw data relating to
the state and control of recording media and raw datacontaining large amounts of information such asvideo data from devices, and it is therefore expectedthat services using large-volume data streams will
emerge.
At NTT Network Technology Laboratories, we aim
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

to create a network that supports IoT services and tocreate and provide network technologies that support
large-volume data streams and that enable an ICT(information and communication technology)-basedsociety as a whole.
2. Characteristics and approach of
IoT data streams
In this article, we define large-volume data streams
transmitted from high-functionality and high-performance devices as IoT data streams. There are two key
characteristics of these IoT data streams: (1) the large
capacity communication occurs intermittently, and(2) different services (purposes) and qualities are
required depending on the service provider or end
user (Fig. 1).
Feature (1) means that centralizing the function thatprocesses the IoT data stream results in extremely
biased traffic. For this reason, we believe that anarchitecture that can minutely expand the minimum
necessary functions to distribute the functions isrequired. In addition, because of feature (2), we
believe that it is important to consider not only thesophistication and diversification of devices but also
network capabilities in order to meet different services and required qualities.
19

Feature Articles

Service provider B

Service provider C

Service provider A• Purpose of reservation• High reliability required

Purpose ofanalysis(1) Large capacity andintermittent communication(2) Different purposes andrequired qualities

High-performance IoT
device of image andcontrol data streams

Immediacy required
High-performance IoT
device of image data
streams
SurveillancecameraDisplay device

Drone

Mobile robot

Fig. 1. Features of IoT data streams.

3. Overview of data stream assist technology

4. Study of specific use case (video data stream)

NTT Network Technology Laboratories has been
studying data stream assist (DSA) technology to
improve the convenience of IoT services by enabling
the network to assist applications and devices according to the characteristics of IoT data streams.
DSA technology flexibly distributes and arranges
the network function modules that operate in lightweight software without preparing dedicated hardware, which intervenes in the processing of communication protocols in the transport and application
layers. With this technology, we achieve a simple
construction and improve the added value of newservices by responding to various applications andrequired qualities for each service provider that provides IoT services and each end user who uses IoT
services.
In addition, to create useful functions and use cases
realized with the DSA technology, we have been
striving to clarify not only the needs of communication carriers but also the cooperation between a specific service provider and our software/network functions (see section 4). For that reason, we are not only
looking at creating innovative elemental technologies
but also integrating existing communication protocols and data formats with commercial technology.

We have been conducting joint research and experiments with the security service provider SECOM
Co., Ltd. since 2016 as part of efforts to study technologies for future IoT services. The introduction ofvarious IoT services is anticipated in the future, and itis therefore expected that social value will be createdwith new IoT services that use images captured bysurveillance cameras, which will have higher resolution than existing devices. However, it is also necessary to study technology related to the network that
supports such new IoT services.
Currently, much of the video data of surveillancecameras is written to the recording medium inside thesurveillance cameras and extracted from the cameras
as necessary for analysis and/or storage purposes.
Furthermore, when acquiring video via a network, it
is necessary to extract multiple videos for different
purposes from surveillance cameras; therefore, congestion can occur in the end users’ LAN (local area
network) and the communication carrier’s network.
We investigated how to use images from surveillance cameras more efficiently and developed anarchitecture that has a function to assist video distribution such as in the edge servers of communication
carriers, so that a video data stream can be duplicatedon a network and used for various purposes such as
analysis, monitoring, and/or storage. To effectively
deliver video data to be used in different applications,
it is necessary to meet three functional requirements:

NTT Technical Review

Vol. 16 No. 9 Sept. 201820

Feature Articles(1) a change in the communication protocol, (2) achange in communication timing, and (3) a change incommunication volume.
4.1 F unctional requirement: communication protocol change
There are two reasons for changing the communication protocol. The first is to adapt to cases where
the required quality differs among multiple destinations that want to distribute videos. For destinations
where videos will be recorded, real-time access is not
required, so we send video data streams using protocols with high data reachability. In contrast, for destinations where videos will be viewed in real time, wesend video data streams using a protocol that emphasizes real-time functionality.
The second reason is to adapt to cases where different protocols can be used for the destination and forthe sender that delivers the video. There are situations
in which the types of protocols that can be used by thereceiver are limited due to the fact that there are few
protocols supported by certain kinds of software suchas the media player operating on a device, and also
because users often prefer to use widely popular protocols such as the Hypertext Transfer Protocol(HTTP). With surveillance cameras, it is difficult toadapt to new protocols because the replacement frequency of such cameras is very low. The protocol
used also depends on the compatibility between the
protocol and the hardware.
4.2 F unctional requirement: communication timing change
There are two reasons for changing the communication timing. The first is the need to send video data
streams according to the state of the network to thedestination where the video data stream will be distributed. When the network is congested, video data
streams that are not required for real-time capabilities
can be temporarily held back, making it possible toreduce network congestion and avoid retransmission
requests due to video streaming/buffering problems.
The second reason is to use the latest video at a highframe rate backwards in time. It is assumed that videos stored in the destination intended for recording
are stored at a lower frame rate in order to reduce thestorage capacity. However, to quickly confirm thecontent in videos when accidents or incidents occur,
it is desirable to have high frame rate videos. Therefore, the communication carrier temporarily stores
video data streams at a high frame rate and delivers
the latest video to the destination as necessary, so thatNTT Technical Review

Vol. 16 No. 9 Sept. 2018the high frame rate video delivery can be performed
without increasing the end user’s storage capacity.
4.3 F unctional requirement: communication volume change
A change in the communication volume may berequired depending on the bandwidth of the network
to the destination and/or the image processing capacity at the destination. When radio transmission capabilities are included in the network, the bandwidth isoften narrowed, and congestion occurs when thesender tries to flow traffic at a higher bandwidth.
Also, under the assumption that image analysis isperformed by artificial intelligence, which has
advanced remarkably in recent years, the number ofvideo frames that can be analyzed per unit time varies
depending on the analysis time. For example, if ittakes more than 100 ms to process one video frame,
image analysis cannot be done at more than 10 frames
per second (fps); therefore, no more video frames areneeded. Furthermore, even when people watch video
in monitoring applications, image delivery exceeding
30 fps is unnecessary.
These three functional requirements must be
achieved without transcoding video data at the network side. Many in-market devices or software thatenable changes in communication protocols, communication timing, and communication volume havehigh capacity that enables connection of many surveillance cameras and/or viewing devices, as well as
various functions such as object recognition in videos. However, such equipment is expensive, as it
requires dedicated hardware or many computational
resources. In addition, there are cases where transcoding is done, and changes are made to the image
quality and the captured content. Furthermore, as theconventional system architecture is not designed considering dispersed and/or divided functions, the system needs to be deployed on a physical or virtual
machine. For these reasons, the computational
resources required to operate unnecessary functions,and the scalability of handling an increasing numberof IoT devices such as surveillance cameras are issues
that need to be addressed.
In contrast to the existing technology as describedabove, the proposed technology enables us to change
the communication protocol, communication timing,and communication volume without decoding theinformation, by replicating a video data stream andappropriately distributing it to multiple destinations
through implementation of a finely decentralized
network function.
21

Feature Articles

Service

Information on video content

Network

Ethernet

V

P

IP

X

CC

UDP/TCP

M

RTP

PT

PayloadSequence number

Timestamp
SSRC

Video frame detectedfrom sequencenumber and timestamp

CSRC
Extended header (optional)

Changing communication protocol, timing, and volume
from information contained in RTP header
RTP where network and service cooperate to create value
CC: CSRC count
CSRC: contributing source identifier
IP: Internet Protocol
M: marker

Adding Information such as
movement in video using
extended header

P: padding
PT: payload type
SSRC: synchronization source identifier
TCP: Transmission Control Protocol

UDP: User Datagram Protocol
V: version
X: extension

Fig. 2. Application example of network and service cooperatively using RTP.

5. Video DSA technology
This section explains the functions used to satisfy
the above requirements and the system that manages
these functions.
We have assumed the use of the Real-time Transport Protocol (RTP) as an appropriate layer to construct the functions for the three functional requirements without video transcoding. Most cameras
support RTP, which is suitable for transmitting a realtime stream, and the Real-time Streaming Protocol(RTSP), which controls the stream.
A usage example of an RTP header used cooperatively between a network and a service is shown in
Fig. 2. The RTP header contains information on thetimestamp, sequence number, media codec, and otherdetails, but it does not have information on the video
content. However, we can detect or obtain the end of
the video frame and the time the video frame was
generated by using the information in the header.
Furthermore, an RTP extension header enables us to
add more specific information such as a flag indicating the motion of some objects in the video. Such
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

information can be used to judge whether or not tostream the video, thereby reducing the amount of traffic.
RTP is designed as the protocol above UDP (User
Datagram Protocol), but RTSP interleave enables us
to utilize TCP (Transmission Control Protocol) as the
protocol under RTP. Therefore, we can make the mostuse of the features of RTP and change the under-layer
protocols, the timing of communication, and theamount of traffic without decoding the video. Thus,
RTP can be said to be the layer where the network andthe service cooperate and create value for each other.
The difference between the conventional approachand our proposed approach in the situation where avideo stream is conveyed with changes in the communication protocol, communication timing, andcommunication volume corresponding to the destination is shown in Fig. 3.
In the conventional approach, video streams transmitted from surveillance cameras are decoded andre-encoded at the intermediary entity and then conveyed to each device (Fig. 3(a)). While the existing
technology needs to transcode video in the intermediary22

Feature Articles

Display
deviceEncoder
Surveillancecamera30 fps

30 fps…

Decoder

Decodedvideo

Display
deviceAnalysisserverEncoder
5 fps
Encoder

PersistenceserverVideo
recorderCopy and distributevideo as a device orsoftware.

An intermediary entity(a) Existing system

Distributed intermediary entities
Display
devicePacketdistribution
PacketSurveillancecamera 30 fps distribution

30 fpsPacketfilterAdoption of
distribution, filter,
and/orreservation
based on RTP
packets

Packetreservation

5 fps

Display
deviceAnalysisserverPersistenceserverPossible to distribute
each processing
function(b) Proposed system

Fig. 3. Comparison of existing and proposed system architectures.

entity, our technology does not do so. Instead of transcoding, our technology changes the communication
protocol, communication timing, and communication
volume corresponding to the destination by handling
RTP packets of one video stream; ensuring distribution of flow, which duplicates RTP packets andchanges their under-layer protocols [1], applying afilter, which drops some RTP packets to adjust theframe rate, and implementing reservation of packets
to store the video stream as RTP packets, but not as
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

video containers (Fig. 3(b)).
An example of the operation flow of the DSA technology is shown in Fig. 4. These functional modules
are designed to rapidly process RTP packets. In addition, because this technology handles each RTP
packet, if packets are encrypted as SRTP (Secure
RTP), the distribution function and the filter functionin Fig. 4 do not need to have encrypted keys. These
functional modules are constructed to enable pluggability, and they connect to each other like a pipeline.
23

Feature Articles

SDP is extracted from the packets
flowing from the surveillance camera,
and information is distributed for the
distribution of the shunted video.
Example of SDP
v=0
o=alice 20202 IN IP4 192.168.10.100s=c=IN IP4 192.168.10.200
t=2873397496 2873404696
a=recvonly
m=video 51372 RTP/AVP 99
a=rtpmap:99 h263-1998/90000~~~~~~

Copy according to
the number ofdestinations.

Media
information
management

Distribution

SurveillancecameraDestination
Destination
FilterDistribution
Destination

Copy only stream control
packets.
Copy only video packets.

Required quality offrame rate

Packets belonging to unnecessary
framesDiscard based on packet
header.

Flow of stream control packets
Flow of video/voice packets
Flow of stream control and video/voice packets
Stream control packet
Video packet
Voice packet
SDP: Session Description Protocol

Fig. 4. Workflow of data stream assist.

This enables us to add new functions and to scale out
with ease.
There are some advantages in processing packetby-packet if we can use the semantics of the data
format loaded on the RTP packet payload, for example, protocol conversion of JPEG over RTP fromRTSP to HTTP or ROS (Robot Operating System),and clipping a specific area from an image.
6. Field trial
To provide our modules dynamically, we haveadopted Docker [2] as the environment in which theprocesses run and Kubernetes [3] as the orchestratorof containers in the current prototype system. In thefield trial that began in December 2017 [4, 5], we
NTT Technical Review

Vol. 16 No. 9 Sept. 2018clustered the physical machines at some central
offices (COs) by using Kubernetes and deployed containers dynamically. An overview of the trial is
depicted in Fig. 5. We confirmed through the trial
using 4K quality surveillance cameras that sufficientavailability of our proposed approach was achieved
by deploying functional modules based on containers, and that utilizing COs (or edge-computing platforms) was effective in terms of low latency and distributed processing.
When the target video data stream is registered by
the user of the camera on our system, containers are
deployed based on declarations about physicalmachines and regions, and a process that manages
media information regarding the data stream takes
place. Then, in correspondence to requests from24

Feature Articles

Datacenter
Inside CO

Receiving server

Serverloaded DSA
VPN apparatus(CPE)

VPN apparatus(CPE)

Utilization of CO asedge computing platform

Network of NTT EAST

NGN

CO C
NGN
CO A

CO B

Base B

Base A
VPN apparatus(CPE)

4K surveillance camera(multiple devices)
CPE: customer premises equipment
NGN: Next Generation Network

Base C

VPN apparatus(CPE)

VPN apparatus(CPE)

Display PC

Display PC

PC: personal computer
VPN: virtual private network

Fig. 5. Network configuration of demonstration experiment.

devices such as a viewing terminal, a function process in a related container boots up and duplicates thedata stream. The duplicated data streams are transmitted to other functions, and the communication
protocol, communication timing, and communication
volume are changed. The cooperative operation ofthese functions is achieved with the Advanced Message Queuing Protocol (AMQP)*1.
A series of actions, registration of the video data
stream, container deployment, and the booting process in response to requests are shown in Fig. 6. The
location of functions is provisioned by a stream management function.
We demonstrated the prototype system and discussed new use cases for this technology in a projectof ATII (APAC Telecom Innovation Initiative)*2 [6].
We also confirmed that it was possible to achievesmart buildings by integrating the technology withexisting systems.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

7. Future prospects
IoT data streams do not only contain video. A
stream of raw data used for actuation and sensing canbe used to control robots and drones. At the NTT
R&D Forum held in February 2018, the concept ofmaintaining low latency by utilizing multiple routes
for raw data obtained from actuation and sensing of
haptic devices enabling touching of objects in virtual
space was exhibited. In the future, when high-performance devices become more widely available, it isexpected that services accompanying new IoT data
streams will emerge.
In our R&D, we aim to realize new IoT services incollaboration with service providers by creating new*1 AMQP: An application layer protocol of message-oriented middleware.
*2 ATII: An R&D initiative to realize virtual infrastructure technology by improving communication services in the APAC (AsiaPacific) region and creating new network services after 2020.

25

Feature Articles

Information ofsurveillance cameraand expansion ofcontainer

API server

Servicemanagement

API server

Registration
information
management

Streammanagement

Registration
information
management

Servicemanagement

Expansion ofcontainer using
Kubernetes

API serverStreammanagement

Activation of function
module in container
on receiving arequest from a device

ModuleSurveillancecameraSurveillancecameraStreammanagement

ModuleDisplay
deviceAnalysisserverRegistration
information
management

Servicemanagement

ModuleRecorderSurveillancecameraActivation of DSA
function based on
the location

ModuleDisplay
deviceAnalysisserverRecorder

AMQP

Container

kubectl
RTSP/HTTP request

Processing module(DSA functions)

RTP stream

Management function

API: application programming interface

Fig. 6. Container deployment and process activation.

technologies, improving existing technologies andinfrastructures, and integrating them.

[5]

References

[6]

[1]

[2]
[3]
[4]

N. Higo, R. Ishibashi, Y. Sueda, Y. Takita, Y. Hamaishi, and Y. Kaieda,“A Proposal for the Distributary Function to Assist Multi-purpose
Usages of Data-streams,” IEICE Tech. Rep., Vol. 117, No. 33, pp.
5–10, 2017.
Docker, https://www.docker.com/
Kubernetes, https://kubernetes.io/
NTT press release issued on December 19, 2017 (in Japanese).
http://www.ntt.co.jp/news2017/1712/171219a.html

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

Focus on the News, “SECOM x NTT Collaboration Achievement
Began Field Trials of Network Assist Function Converting Communication Data According to Purpose,” NTT Technical Journal, Vol. 30,
No. 5, pp. 55–57, 2018 (in Japanese).
T. Kuwahara, I. Hitoshi, and K. Suzuki, “Global Collaboration Initiatives Revolutionizing Research and Development of Network Technologies,” NTT Technical Review, Vol. 16, No. 6, 2018.
https://www.ntt-review.jp/archive/ntttechnical.php?contents=
ntr201806fa7.html

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

26

Feature Articles

Naoki Higo

Researcher, Innovative Network Technology
and Collaboration Group, Network Architecture
Design and Promotion Project, NTT Network
Technology Laboratories.
He received a B.S. and M.S. in control engineering and statistics from Tokyo Institute ofTechnology in 2011 and 2013. He joined NTT
Network Technology Laboratories in 2013,
where he conducted research on softwaredefined networking/network functions virtualization and network architecture for future IoT.
His current research interest is multi-access edge
computing. He is a member of the Institute ofElectronics, Information and Communication
Engineers (IEICE).

Takuma Tsubaki

Researcher, Innovative Network Technology
and Collaboration Group, Network Architecture
Design and Promotion Project, NTT Network
Technology Laboratories.
He received a B.E. and M.E. in electrical engineering from Yokohama National University in2012 and 2014. He joined NTT in 2014 andworked on network reliability evaluation andnetwork design for disaster resilience. He is currently researching multi-access edge computing.
He is a member of IEICE.

Toshimitsu Tsubaki

Senior Research Engineer, Innovative Network
Technology and Collaboration Group, Network
Architecture Design and Promotion Project,
NTT Network Technology Laboratories.
He received a B.S. and M.S. in geophysics
from Tohoku University, Miyagi, in 1994 and1996. He joined NTT in 1996 and was involved
in R&D of medium access control for broadband
wireless access systems, RFID (radio frequency
identifier) tagging systems, and non-contact
high-speed transmission systems. His current
research interests are network assistance technologies for IoT services. He is a member of
IEICE.

Takeshi Kuwahara

Senior Research Engineer, Supervisor, Group
Leader, Innovative Network Technology andCollaboration Group, Network Architecture
Design and Promotion Project, NTT Network
Technology Laboratories.
He received a B.E. and M.E. from Waseda
University, Tokyo, in 1995 and 1997. Since joining NTT in 1997, he has been engaged in R&D
of ATM (asynchronous transfer mode) networks,
IP-VPNs (Internet protocol virtual private networks), cloud systems, network security, andedge computing technologies. He was in chargeof telecom carrier relations regarding network
R&D while based in Washington, D.C., USA,and led the establishment of ATII while in his
current position. He is a member of IEICE.

Kohjun Koshiji

Research Engineer, Innovative Network Technology and Collaboration Group, Network
Architecture Design and Promotion Project,
NTT Network Technology 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/management of telecommunication networks. He is currently involved in multi-access edge computing.
He is a member of IEICE.

NTT Technical Review

Vol. 16 No. 9 Sept. 201827

Feature Articles: Research and Development Initiatives
for Internet of Things Implementation

Utilization of Edge Computing and
IoT Sensors in Hierarchical Weather
Forecasting System
Ryota Nakada, Koya Mori, and Noriyuki Takahashi
Abstract

NTT and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) began collaborative research on a hierarchical weather simulation system using the Earth Simulator and edge computing
in 2016. This project promotes the creation of new technology for the interworking of geographically
distributed Internet of Things (IoT) sensors, regionally located edge computing, and the Earth Simulator
that is capable of large-scale weather simulation. The project also promotes the development of fundamental technology for supporting various IoT services.
Keywords: edge computing, IoT sensors, hierarchical weather simulation

1. Introduction
The Internet of Things (IoT) has been attracting
attention because it connects all kinds of things to theInternet and makes various kinds of sensing possible.
The future IoT society is expected to bring innovationin various industries by enabling the collection andanalysis of a variety of sensor data via a network
independently of time, place, or environment. Whilesome IoT sensors such as thermometers transmit lowvolume data, others produce large-volume data suchas still-image or video data from infrared cameras.
The sensing frequency and the number of sensors
installed also vary with the service provided.
From the viewpoint of using sensor data in services,
some data are used only regionally, and other data are
aggregated for analysis on a national scale in thecloud. One use case that requires such aggregation ofdata that has different regional dispersion requirements is weather forecasting.
2. Weather forecasting simulation
using IoT data
Weather forecasting is an important key in the construction of the IoT society. Highly accurate real-time
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

weather forecast data are expected to be useful inmany fields. In addition to obvious applications in the
primary industries of agriculture and fishing, applications in the areas of automobile and rail transportation and sports stadium industries are also expected.
A simple way to increase the accuracy of weather
forecasting is to increase the resolution of the model.
In simulations such as weather forecasting models,
the target spatial region is divided into a constantinterval grid, and calculations for each unit of the gridare done according to relationships with the neighboring units. A grid that has smaller units enables ahigher-resolution simulation that closely models the
behavior of the actual environment, but there is atrade-off between grid resolution and computationalload.
For example, for a simulation in three-dimensional
space, reducing the length of a grid unit by one-halfincreases the amount of grid calculation by a factor ofeight (two to the third power). It is also necessary to
reduce the time interval for the calculations by half,
so the total computational cost increases by a factorof 16 (two to the fourth power).
Therefore, highly accurate prediction for all locations in the space requires a huge amount of calculation. However, it is not necessary to make highly
28

Feature Articles

Earth Simulator

MSSG© JAMSTECInternet
MSSG

Edge server© JAMSTEC

IoT sensor
MSSG: Multi-Scale Simulator for the Geoenvironment (MSSG) weather forecasting software.

Fig. 1. Hierarchical weather simulation system.

accurate predictions in all locations. For predictions
relevant to the agricultural industry, for example, it issufficient to cover agricultural land areas, and forautomotive transportation, it is sufficient to cover
expressways and national highways. If it were possible to achieve highly accurate local weather forecasting simulations in addition to the conventional largearea simulations, it would be possible to provide
sufficient weather forecasting at low cost.
Conventional large-area weather forecasting simulations are based on data for large regions; such data
may consist of atmospheric pressure distributions andweather satellite images. For local weather forecasting, local on-site data are input to the simulation inreal time. It is possible to provide highly accurate
local weather forecasts by using IoT sensor data suchas local sky images and data from local temperature
sensors. Furthermore, the highly accurate local
weather forecasting data can be used to improve theaccuracy of regional simulations.
NTT and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) [1] began collaborative research on a hierarchical weather simulation
system using the supercomputer Earth Simulator*1and edge computing*2 in 2016 [2].
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

The collaborative research reported here involves
construction of a hierarchical weather simulation
system that looks toward a future IoT platform bycombining IoT sensors, edge servers that serve as
specialized regional computing resources, and alarge-scale Earth Simulator computing system. We
are using that system to test the effect of IoT sensor
data in local weather simulations and will continue towork on identifying and solving problems of the system as an IoT platform [3].
3. Hierarchical weather simulation system
The hierarchical weather simulation system (Fig. 1)
combines IoT sensors, edge servers that aggregate thedata from the sensors, and the Earth Simulator supercomputer—all types of equipment that have different*1 Earth Simulator: A large-scale computing system operated by
JAMSTEC that is used for research in various fields of maritimeand earth sciences, including predictive global warming models
and geological changes.
*2 Edge computing: A distributed computing scheme that places
servers between users and the cloud at locations that are physically near the users to enable execution of applications and someof the processing by cooperation between terminals and thecloud.

29

Feature Articles© OpenStreetMap contributors

Calculation range: national scale
Grid size: 100 km scale© OpenStreetMap contributors

Calculation range: city scale
Grid size: 100–300 m scaleFig. 2. Weather forecasting simulations on various geographical scales by MSSG.

specifications and functions—in a multilevel configuration. The hierarchical weather simulation system
is run on the Multi-Scale Simulator for the Geoenvironment (MSSG) weather forecasting softwaredeveloped by JAMSTEC. MSSG is capable of running weather forecasting simulations on various geographical scales (Fig. 2). The specified calculation
range is divided into a grid, and the units of the grid
serve as units for simulation of temperature, humidity, atmospheric pressure, wind direction, wind speed,
sunshine, and precipitation. The grid unit can be set
according to the computational resources that areavailable. If the grid is made smaller for the sameamount of computational resources, the simulation is
performed on a local scale, and if a larger unit is used,
the simulation is run on a regional scale.
Another major feature of MSSG is the data assimilation function, which makes it possible to integrate
observation data into the simulation results. The
accuracy of prediction by simulation can be improvedby inputting observation data within the range of thesimulation. Specifically, temperature, wind direction,and other weather data can be assimilated, and in
addition, sky image data can also currently be used by
MSSG. In the future, it will also be possible to use theassimilation function for a wide variety of dataacquired by IoT sensors in weather forecasting.
Next, we consider the role of the hardware in eachlevel of the hierarchical weather simulation system.
The top-level Earth Simulator is a supercomputer
operated by JAMSTEC and is used for large-scalecomputations that are required for marine and Earthscience research in areas such as global warming andgeological changes. MSSG runs on the Earth SimulaNTT Technical Review

Vol. 16 No. 9 Sept. 2018

tor and divides the entire globe into a grid that hasunits of about 10 km for weather forecasting simulations.
The edge servers that constitute the hardware forthe middle level of the system are distributed overeach region. It is assumed that the edge servers will
be located near users within NTT’s wired networkand mobile network base stations in the future. In our
joint research, the edge servers run MSSG in thesame way as does the Earth Simulator. For the MSSG
on the edge servers, the calculation range is narrowed
to a grid unit size of several hundred meters to effectively use the computational resources in performing
a local weather simulation.
The IoT sensors used for the bottom level are
weather observation sensors, which measure basic
weather data including temperature, humidity, precipitation, sunshine, wind direction, and wind speed
at fixed time intervals and send the data to the edge
servers (Fig. 3).
In the hierarchical weather simulation, data areassimilated and exchanged between adjacent levels in
the hierarchy. The IoT sensors send data to the edge
servers, which assimilate the data and run highly
accurate local weather forecasting simulations. Theedge servers exchange simulation results with the
Earth Simulator. The local weather simulations canobtain boundary conditions for the margins of theircalculation ranges by obtaining weather information
outside their computation range from the regional
weather simulations. The wide-area weather simulations can obtain the highly accurate weather simulation information from particular regions.
After the accuracy of wide-area simulations is30

Feature Articles

Fig. 4. Result of 300-m grid units of local simulation.

Fig. 3. Weather observation sensor.

improved by assimilating data from the results oflocal simulations, data from the improved wide-area
forecast results can be assimilated back into the local
simulations. The middle latitudes in which Japan is
located are known for weather that changes fromwest to east due to westerly winds. Wide-area simulations can use data assimilated from local simulations
to good effect with respect to such temporal changes.
A nationwide distribution of IoT sensors and edge
servers would make it possible to provide weather
forecast data to locations of high business value suchas dense population centers, areas in which primaryindustries are concentrated, riverine areas, national
highways, and stadiums.
4. Effectiveness of hierarchicalweather simulation
We used the hierarchical weather simulation system to conduct actual local weather forecasting simuNTT Technical Review

Vol. 16 No. 9 Sept. 2018

lations. The data from weather sensors and the resultsof wide-area simulation by the Earth Simulator wereassimilated by edge servers. An example of the simulation results is shown in Fig. 4, which is a heatmapthat shows the differences in temperature for the
300-m grid units of a local simulation for a sunny
winter day, where we can see that there are temperature changes in each grid unit.
The temperature changes over time for the grid unit
indicated by the red pin in Fig. 4 are plotted in thegraph shown in Fig. 5, where dark blue data points
are the forecast results for this hierarchical weather
simulation, the light blue data points are the forecast
results for a conventional simulation that does not use
assimilation data from the sensors or from the Earth
Simulator, and the red data points are actual datameasurements (ground truth values) obtained by the
Automated Meteorological Data Acquisition System(AMeDAS) operated by the Japan Meteorological
Agency. We can see from the figure that using assimilation of the sensor data and data from the wide-areasimulations results in forecast values that are close to
the actual measured values.
5. Future prospect
We have described the principle of a hierarchicalweather forecasting system that combines the Earth
Simulator and edge computing. One problem forpractical application of IoT in weather forecasting isinstallation of IoT sensors in non-ideal situations.
Although the sensors used in the experiment reported31Temperature (°C)

Feature Articles

11.00
10.00
9.00
8.00
7.00
6.00
5.00
4.00
3.00
2.00
1.00

Hierarchical weather simulation using IoT sensors
Conventional weather simulation notusing IoT sensors
Measurement data from
AMeDAS–1.00
Feb. 3 09:00

12:00

15:00

18:00

AMeDAS: Automated Meteorological Data Acquisition System

Fig. 5. Comparison of measurement data and simulation.

here were installed in ideal environments, we cannot
expect that all of the many IoT sensors used will beproperly installed and maintained.
To address this problem, we are investigating methods of determining sensor data reliability through alearning process based on past data to increase thevalue of IoT sensor data. We will also continue toexplore generalized quantitative measures of the true
value of an IoT platform for business by testing theeffect of increasing the amount of measured data on
the amount of sensor data and simulation results todetermine how much value is generated with respect
to the cost of installing edge computing resources.

Ryota Nakada

Research Engineer, Ubiqutous Network System Research Group, NTT Network Innovation
Laboratories.
He received a B.E. and M.E. in mathematics
from Tokyo University of Science in 2008 and2010. He joined NTT Network Innovation Laboratories in 2010 and researched a high resolution
image transport system. He moved to NTT
WEST in 2013, where he studied an indoor location information system. He rejoined NTT Network Innovation Laboratories in 2016 and has
been researching edge computing and taking partin a collaborative research project with JAMSTEC.

References
[1]
[2]
[3]

Website of JAMSTEC, http://www.jamstec.go.jp/e/
NTT press release issued on February 9, 2016 (in Japanese).
http://www.ntt.co.jp/news2016/1602/160209b.html
R. Onishi, K. Mori, F. Araki, K. Itakura, S. Kawahara, R. Nakada, N.
Takahashi, and K. Takahashi, “Smart Weather Forecasting by Computing Network Comprising the Earth Simulator and Edge Servers,”
JpGU-AGU Joint Meeting 2017, Chiba, Japan, May 2017.

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

Noriyuki Takahashi

Senior Research Engineer, Supervisor, Ubiquitous Service Systems Laboratory, NTT Network
Innovation Laboratories.
He received a B.E. and M.E. in informationengineering from Kyoto University in 1990 and
1992. He joined NTT LSI Laboratories in 1992.
He has been in his current position since 2001.
His research interests include routing mechanisms, adaptive networking systems, and architecture design of future networks. He is a member of IEICE and the Institute of Electrical andElectronics Engineers.

Koya Mori

Senior Research Engineer, NTT Network Innovation Laboratories.
After joining NTT in 2004, he researched anddeveloped an IoT application based on software
technologies such as the OSGi (Open Services
Gateway Initiative), OpenStack, and edge computing. He is a member of the Institute of Electronics, Information and Communication Engineers (IEICE).

NTT Technical Review

Vol. 16 No. 9 Sept. 201832

Regular Articles

New Transport QoE-control
Technology Enabling High-definition/
High-presence Content Distribution
Takafumi Okuyama, Ken-ichi Endo, Takuto Kimura,
Arifumi Matsumoto, Toshihito Fujiwara,
and Yasunobu Kasahara
Abstract

NTT is striving to support the growing demand for high-definition video delivery services and istherefore developing technologies for optimizing the deployment of servers for content providers andtelecom operators and their communication networks and for providing a new means of delivery control.
This article introduces content delivery network technology for achieving economical and high-quality
delivery of high-definition, high-presence video content.
Keywords: CDN, QoE control, multicast conversion

1. Introduction
The development of 4K/8K video coding schemes
and high-definition user terminals has led to the introduction of services for delivering various types ofhigh-capacity video content over the network. In theexisting video content delivery services, content providers cope with the volume of traffic by increasing
the number of servers and the network bandwidth inproportion to the product of content volume and number of users. The amount of content and the numberof users is expected to increase dramatically in the
future market, but the potential expansion in facility
resources is limited. It will therefore be difficult tomaintain or improve the user’s quality of experience(QoE) when viewing video content and to provide
enjoyable services at low cost with this conventional
approach (Fig. 1).
This situation calls for a new mechanism that can
improve the efficiency of using and operating facilities, by using more appropriate delivery information.
For example, this might necessitate changing thedelivery settings according to the type of terminal or
NTT Technical Review

Vol. 16 No. 9 Sept. 2018

circuit and the network conditions while visualizing
the user’s QoE when viewing video content.
We introduce here high-definition/high-presence
content delivery network (CDN)*1 technology thathas been developed with the aim of providing nextgeneration, high-quality services while controlling
facility expansion. The element technologies for constructing a CDN that are described here are QoE
visualization technology for grasping the user’s stateof video content viewing, QoE control technology for
optimizing the delivery method according to theuser’s usage format and usage conditions, real-timelarge-capacity delivery technology for deliveringlarge-capacity live video in an efficient and stablemanner, and manifest control technology for achieving flexible control of content delivery.
2. QoE visualization technology
To provide users with an effective and enjoyable*1 CDN: A network targeting content delivery. Here, a network fordelivering video content.

33

Regular Articles+

Server expansion

CDN

×
Network bandwidth expansion
Enhancement/expansion of
network facilities

Telecom operator network

SD

…
SD
8K

2K

4K

VR

Higher content capacity
More user terminals
SD: standard definition
VR: virtual reality

Fig. 1. Expansion of capacity and scale in existing content delivery network (CDN).

video content delivery service, it is necessary toobserve the user’s QoE when viewing video content
and to control the CDN appropriately. This makes thevisualization of QoE essential. Hypertext Transfer
Protocol (HTTP) streaming*2 and the adaptive bit rate(ABR) system have come to be widely used recently
in video content delivery services. In HTTP streaming, the viewing clients play back video content while
downloading pre-divided video data (file segments/
chunks) in sequence and storing the data in a buffer.
Then the ABR system enables the viewing clients todynamically adjust video quality (encoding bit rate)and download timing (pacing) to maintain the user
QoE in accordance with the communication environment.
However, a major deterioration in the communication environment can impair the ABR operation andgive rise to rebuffering, in which buffered data are
depleted, and playback is temporarily suspended,resulting in a drop in QoE. In addition to such ABRbased autonomous operation by the viewing client,
there are also control operations of the delivery server, various devices, and access lines, all of whichmake the visualization of QoE a difficult task.
The QoE visualization technology introduced here
uses a QoE estimation model [1] proposed by the
NTT laboratories to quantify the QoE of a video content delivery service using ABR. Specifically, thistechnology achieves QoE visualization by equipping
NTT Technical Review

Vol. 16 No. 9 Sept. 2018the viewing client receiving video data with a function for collecting the video/audio encoding bit rate,
video resolution, frame rate, and history of rebuffering, and by inputting such information collected
while viewing video content into the QoE estimation
model. At present, this model can estimate QoE forvideo content with Hi-Vision (high-definition television) screen resolution (1920 horizontal × 1080 vertical pixels) or less. Research and development of QoE
estimation technology for high-resolution video content such as 4K/8K video is in progress.
The visualization of QoE makes it possible torespond quickly to a user’s quality inquiry throughoperational actions such as assessment of conditions
and cause analysis. In addition, such visualized information can be provided to content-delivery clients asevidence of the service state.
3. QoE control technology
In video content delivery services, both users andcontent providers need to maintain quality when

*2 HTTP streaming: A method for achieving live/on-demand video
delivery using an ordinary HTTP server instead of a special video
server. HTTP Live Streaming (HLS) and Dynamic Adaptive
Streaming over HTTP (DASH), also known as MPEG (Moving
Picture Experts Group)-DASH, are examples of HTTP streamingthat have found widespread use.

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Regular Articles

Video delivery technology that controls the balance between QoE and traffic volume

Average bit rate
(traffic volume) Video bit rate needed to
improve QoE sharply rises.
3.4 Mbit/s
Traffic volume is greatly
reduced by approachingtarget QoE.

QoE (estimated MOS): 4.8
Average bit rate: 3.4 Mbit/s
A difference in QoE, while not that large, still
generates a large difference in traffic volume.

1.0 Mbit/s

QoE
4.2
4.8 (estimated
MOS)
Target QoE

QoE (estimated MOS): 4.2
Average bit rate: 1.0 Mbit/s

Relation between QoE and bit rate

Fig. 2. QoE control technology.

delivering video content and to reduce traffic costs
for delivery. The user, on one hand, feels dissatisfied
if the quality of video content drops excessively, but
if quality rises to a level higher than necessary, thetraffic volume increases, resulting in higher communication charges. Therefore, it is necessary to reduce
the traffic volume while maintaining a certain level ofquality. The content provider, on the other hand,should prepare for a rapid increase in content volume
or number of users by reducing the traffic volume
within a range that is not unsatisfactory to the user.
QoE control technology meets these needs by effectively manipulating the balance as desired between
quality and accompanying traffic.
QoE control technology controls this balance byusing the relationship between bit rate and QoE. This
relationship between traffic volume (average bit rate)and QoE (estimated mean opinion score (MOS)*3) isshown in Fig. 2. As shown, raising the QoE from 4.2
to 4.8 requires the bit rate to be increased by morethan three times from 1 Mbit/s to 3.4 Mbit/s. This
tells us that in a high QoE region, a threefold increasein bit rate does not result in a dramatic improvement
in QoE. Therefore, we make use of such QoE characteristics by setting a QoE target value given by thecontent provider or user. Our QoE control technology
controls the bit rate of video content to achieve theminimum QoE delivery satisfying that target value.
This prevents the QoE and traffic volume frombecoming higher than necessary. In addition, perNTT Technical Review

Vol. 16 No. 9 Sept. 2018

forming optimization calculations here makes it possible to select a bit rate that generates the least amountof traffic for the same QoE.
This technology enables the provision of a video
delivery service that can keep traffic cost to a minimum while maintaining service quality at a level
required by the content provider or user. Therefore,
we expect this technology to reduce network load
significantly while maintaining QoE. In fiscal year
2017, we performed a field trial using NTT Plala’s
video delivery service for smartphones and succeeded in demonstrating the effectiveness of this technology in an actual service.
4. Real-time large-capacity delivery technology
Real-time large-capacity delivery technology
achieves efficient and stable delivery of large-scale
live/linear video content. Ordinary video delivery
systems are achieved by sending HTTP-based unicast
traffic between the video delivery server and terminals. However, if this ordinary scheme is applied todeliver real-time large-capacity video data as in thelive delivery of popular content, viewing demand can*3 MOS: A value quantifying the level of quality subjectively felt byhumans with respect to a target of evaluation (audio/video media,etc.) based on an opinion score as specified by ITU-T (International Telecommunication Union - Telecommunication Standardization Sector) Recommendation P.800.

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Regular Articles

Viewing request
Unicast (video)
Multicast (video)
Network

Live content provider
Manifest server

HTTP accessViewing request
Live viewer (each viewer)

Provides guidance to HTTP
access edge servers (lower)

Edge server(lower)Viewing request(one stream only) Edge server(upper)Edge server(lower)Delivery server(general-purpose HTTP server)

Unicast(one stream only)

Multicast(one stream only)

Unicast to multicast
conversion

No need for many copies
of same content

Multicast to unicast
conversion
Unicast(each viewer)
Improves usage efficiency of facility resources(network bandwidth, delivery servers)
Achieves stable delivery of high-quality video

Fig. 3. Unicast/multicast conversion technology.

easily peak, thereby greatly increasing the load on
facilities such as delivery servers and the network
itself. Such facilities may not be able to bear that
load, resulting in a severe deterioration in QoE.
In contrast, real-time large-capacity delivery technology delivers video data via multicast*4 only in the
CDN, while leaving the HTTP-based unicast interface unchanged at each delivery server and terminal.
This scheme avoids duplicate delivery of the same
video content, which improves facility usage efficiency even for the servers of content providers andachieves stable content delivery (Fig. 3).
Specifically, this technology involves placing an
upper edge server at the network entrance facing thedelivery server, converting traffic from unicast to
multicast, placing multiple lower edge servers at the
network exit connected to terminals on the opposite
side, and converting the traffic from multicast to unicast. The video content is transferred via multicast in
the network zone between the upper edge server andlower edge servers. Here, instead of relying on server
performance as in the conventional method, data arecopied at multicast-supporting routers within the netNTT Technical Review

Vol. 16 No. 9 Sept. 2018

work, which makes for efficient video delivery.
Additionally, for the same video content, traffic
from the delivery server to the upper edge server andfrom the upper edge server to the lower edge servers
consists of a single stream regardless of the numberof users viewing content simultaneously. This technology can therefore drastically reduce traffic in the
network compared to the unicast-only scheme while
delivering high-quality video in a stable manner toeach user. Moreover, while a system using conventional multicast technology requires delivery servers
and terminals that support multicast transmission,
this technology enables servers and terminals to use
the existing HTTP-based system, thereby easing theburden of procuring and installing new equipment for
both content providers and viewing users.
5. Manifest control technology
Manifest control technology can achieve flexible*4 Multicast: The simultaneous transmission of a single set of datato specific terminals or switches.

36Regular Articles

Policy control
server

DNS

Delivery instructions
based on policy

Manifest file specifies selectable range ofvideo quality, composition, and delivery
servers of segment files.

Manifest
serverAchieves dynamic content delivery
combined with conventional technologies(DNS method etc.)

Manifest file(content overview)– title/streaming type/media type/length(delivery server URL)
(audio/video data)– audio data/video data
information (coding/bit rate)(segment information)
1 start=0s, http://~2 start=10s, http://~3 start=20s, http://~

Delivery server #C Delivery server #B(video-ad dedicated) (high-quality use)

Delivery server #A(standard-quality use)

Terminal

Client can be directed to dedicated servers during
specific video intervals (advertisements etc.).

Content/quality can beappropriately switched foreach user.

DNS: domain name system
URL: uniform resource locator

Fig. 4. Manifest control technology.

control of content delivery such as by specifying the
bit rate of video content to the client in QoE control
technology and directing the client to specified edge
servers (lower) in real-time large-capacity delivery
technology.
When a user makes a request to view video content,
the client will request video-content files. For thispurpose, major HTTP streaming schemes use amanifest file (e.g., a playlist in HLS or an MPD(Media Presentation Description) in MPEG-DASH).
A manifest file contains information on how thevideo content is divided into segment files at whatlevels of video quality and from what locations thesegment files should be requested [2]. With manifest
control technology, the manifest server, on receivinga request from the client for a manifest file, sends thefile based on the client’s identification information.
This approach achieves efficient delivery control thatis dynamically operated (Fig. 4). Specifically, manifest control technology achieves flexibility throughdiverse types of delivery control such as switchingcontent, limiting the selectable range of video quality
for ABR, directing the client to dedicated servers during specific video intervals (advertisements etc.), andload balancing of global cache servers.
With conventional technology, the domain namesystem (DNS) directs the client to the CDN cache
NTT Technical Review

Vol. 16 No. 9 Sept. 2018servers where video content files are downloaded
when the client starts to play back content (DNS
method). Here, however, DNS can only roughly identify the client by a group such as Internet service
providers, and it takes time for DNS changes to be
fixed in the network. Thus, the disadvantage of the
DNS method is that it cannot identify the client finely
or handle the load balancing promptly. With this inmind, we combined manifest control with the DNS
method to achieve scalability and fine control.
6. Future development
We are conducting trials of the video content delivery technologies introduced here and will use theresults to continue researching delivery platform
technologies that are essential to the development of
4K/8K video coding schemes and high-definition
user terminals.
References[1][2]

K. Yamagishi and T. Hayashi, “Parametric Quality-estimation Modelfor Adaptive-bitrate Streaming Services,” IEEE Trans. Multimedia,
Vol. 19, No. 7, pp. 1545–1557, 2017.
RFC 6983: “Models for HTTP-adaptive-streaming-aware Content
Distribution Network Interconnection (CDNI),” 2013.

37

Regular Articles

Takafumi Okuyama

Senior Research Engineer, NTT Network
Technology Laboratories.
He received a B.E. and M.E. in information andcomputer sciences from Tokyo Institute of Technology in 2005 and 2007. He joined NTT Service
Integration Laboratories in 2007. From 2010 to2014, he was with NTT Communications, where
he worked as a mobile application engineer. He iscurrently researching and developing a content
delivery network for video streaming, a communication quality analysis/control method for VoIP
(voice over Internet protocol), and video services.

Ken-ichi Endo

Senior Research Engineer, Network Architecture Innovation Project, NTT Network Technology Laboratories.
He received a B.E. and M.S. in electronic engineering from the University of Yamanashi in1984 and 1986. He joined NTT LSI Laboratories
in 1986. He has been with NTT Network Technology Laboratories since 2012, where he isstudying distribution of next-generation video
content.

Takuto Kimura

Researcher, Communication Quality Group,
Communication Traffic & Service Quality Project, NTT Network Technology Laboratories.
He received a B.E. and M.E. in information andcomputer sciences from Tokyo Institute of Technology in 2011 and 2013. He joined NTT in 2013and has been engaged in research of communication quality control. He received the Young
Researcher’s Award from the Institute of Electronics, Information and Communication Engineers in 2017.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

Arifumi Matsumoto

Senior Research Engineer, Communication
Quality Group, Communication Traffic & Service Quality Project, NTT Network Technology
Laboratories.
He received a B.E. and M.E. in information
sciences from Kyoto University in 2002 and2004. His research interests are emerging network technologies such as IPv6, multihoming,and mobility. He is currently researching communication quality control.

Toshihito Fujiwara

Senior Research Engineer, Access Network
Service Systems Project, NTT Access Network
Service Systems Laboratories.
He received a B.E., M.S., and Ph.D. in engineering from the University of Tsukuba in 2002,
2004, and 2011. He joined NTT Access Network
Service Systems Laboratories in 2004, where hehas been researching and developing video delivery and video transmission systems.

Yasunobu Kasahara

Senior Research Engineer, Access Network
Service Innovation Group, Access Network Service Systems Project, NTT Access Network
Service Systems Laboratories.
He received a B.E. and M.E. in electronicengineering from Nihon University, Chiba, in
1996 and 1998. He joined NTT in 1998 and has
worked on the development of optical accesssystems such as asynchronous transfer modesystems, passive optical networks, and layer 2
switches. He is currently involved in research anddevelopment of content distribution technologies
for emerging services.

38

Global Standardization Activities

Standardization of Automation
Technology for Network SliceManagement by ETSI Zero Touch
Network and Service Management
Industry Specification Group(ZSM ISG)
Yoshinori Goto
Abstract

The European Telecommunications Standards Institute established a new Industry Specification
Group (ISG) on Zero touch network and Service Management (ZSM) that is working to produce a set oftechnical specifications on fully automated network and service management with, ideally, zero humanintervention. This article describes the preparation and outcome of the recent ZSM ISG meetings.
Keywords: ZSM, network slice, ETSI

1. Introduction
The new concept called Zero touch network andService Management (ZSM) is gaining attention
from industry experts in the field of network operation. This is the vision that aims to realize fully automated network operation with ideally zero humanintervention, in contrast to the conventional network
operation requiring intensive human effort. The ZSM
standardization is motivated by several underlying
industry trends. For example, introduction of new
network services is delayed because of the human
involvement required in conventional network operation. New features of network services such as network slicing and edge computing will introduce
additional complexities to network operation. Furthermore, maintaining the current level and numberof network engineers is expected to be increasingly
difficult due to demographic changes, particularly indeveloped countries such as Japan.
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Vol. 16 No. 9 Sept. 2018

However, an unprecedented level of automation
will become possible thanks to the development of
new technologies such as network functions virtualization (NFV) and artificial intelligence. In view ofthese trends happening in the industry, the vision of
ZSM has been discussed among members of theindustry, who agreed to request the European Telecommunications Standards Institute (ETSI) to establish a new Industry Specification Group (ISG) todiscuss this emerging subject.
2. Preparation for the new ISG
Preparation work for the new ISG on ZSM started
in the spring of 2017. Employees from Deutsche
Telekom, Ericsson, Hewlett-Packard Enterprise,
Huawei, IBM, Intel, NEC, Nokia, NTT, NTT DOCOMO, Sprint, Telefonica, Viavi Solutions, and ZTE
volunteered their time in this activity. Mr. Klaus Martiny of Deutsche Telekom led this work. The proposal
39

Global Standardization Activities

to establish the new ISG was completed in November
2017 and approved by the ETSI Board.
In parallel with this, employees of telecom operators volunteered to produce the whitepaper that
describes the motivation, industry trends, the necessity of standardization, and priority items of ZSM,
which is available on the ETSI website [1]. ZSM istargeted for 5G (5th-generation wireless systems),
particularly in network slice deployment. NTT has
contributed to making this one of the directions of
ZSM ISG.
3. Discussion at ZSM meetings
The discussion topics and outcomes of the meetings held by this working group are described in thissection.
3.1 Kick-off meeting
The kick-off meeting of ETSI ZSM ISG was held at
the ETSI headquarters in Sophia-Antipolis, France,from January 10 to 12, 2018. This was only one
month after the official establishment of the ISG.
Joining the kick-off meeting were 42 experts from 23
companies around the world, and 28 contributions
from members were submitted. These contributions
introduced the ideas of automation of network operation as well as proposals on the work methods of the
ISG.
The first task of the kick-off meeting was to electthe ISG Chair and Vice-Chairs. There was a consensus among the participants that Mr. Martiny Klaus
was the right person to lead this ISG because of theastute and effective leadership he demonstrated during the preparation work. Thus, Mr. Klaus was elected as Chair of the ISG. There were three candidates
for two Vice-Chair positions, and thus an election was
carried out. Voting rights in the election were limited
to the Founding Members, which are the companies
listed as supporting companies, including NTT, in the
proposal of the establishment of the ISG. This privileged status given to the Founding Members enabled
NTT to push its idea highlighting network slicing as
an important subject of the ISG.
In this election, NTT contacted the three candidates
and asked them to support the network slice proposal.
All the candidates showed their support for the proposal from NTT. This is a good example that early
involvement is critical for gaining influence in standardization work. The election was held, and Mr.
Toche Christian of Huawei France and Ms. Sprecher
Nurit of Nokia were elected as Vice-Chairs of ISG.
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Vol. 16 No. 9 Sept. 2018

Most of the meeting was spent on brainstorming
discussions on key concepts of ZSM. In the preparation work, the experts had already reached a common
understanding on the objective of ZSM standardization as described in the whitepaper. However, evenamong such experts, there were still various opinions
on the details of ZSM such as, for example, candidate
technologies, likely use cases, and the relationshipwith other technologies. Even a formal definition of
ZSM was heavily debated by the experts.
Furthermore, there were newcomers who were not
involved in the preparation work but who joined after
the ISG was officially established. Some of theseexperts are not regular participants in telecommunication standardization efforts but work in other industries such as the computer industry and have different
backgrounds. This was a good exercise to get to knoweach other and create a constructive atmosphere.
ZSM ISG established the Network Operator Council (NOC), for which participation is limited to network operators. NOC is an advisory group expected
to provide recommendations to the ZSM ISG fromthe viewpoint of network operators, although it has
no binding power on the outcomes of the ZSM ISG.
In the NOC meeting held as part of the ZSM ISG
kick-off meeting, Dr. Khan Ashiq was elected as
NOC Chair, and Dr. Manning Serge was elected as
NOC Vice-Chair. The telecom operators in the NOC
meeting exchanged their views and expectations of
ZSM ISG.
At the end of the meeting, the Work Items (Table 1)
were approved based on the discussions during thiskick-off meeting. Network slice was identified as animportant subject in ZSM; therefore, several Work
Items refer to this issue. A study on automation technology was also included in the Work Items. Standardization work usually starts with requirements
followed by architecture. The ISG follows this format, and these items are given high priority. ISGs in
ETSI produce two types of deliverables, GroupSpecifications (GSs) and Group Reports (GRs). A GS
is a normative document that defines the technicalfeatures of the system being discussed using binding
terms such as “shall,” “should,” and “may.” A GR is
an informative document that gives useful information about the system.
3.2 Second meeting
The second meeting was held at the Nokia Training
Center near Helsinki, Finland, from March 13 to 15,
2018. There were 45 experts from 26 companies participating, and 35 contributions with technical40

Global Standardization Activities

Table 1. Work Items of ZSM-ISG (as of March 2018).
Work Item

GS/GR

Title

Rapporteur

Timing

ZSM001GS

Use Cases and Requirements

Michael Klotz (Deutsche Telekom)

Nov. 2018

ZSM002GS

Reference Architecture

Uwe Rauschenbach (Nokia)

Sept. 2018

ZSM003GS

End to End Management andOrchestration of Network Slicing

Lan Zou (Huawei)

Nov. 2018

ZSM004GR

LandscapeJinhua Wu (ZTE)

Nov. 2018

ZSM005GR

Means of Automation

Andreas Krichel (Hewlett-Packard
Enterprise)

June 2018

ZSM006

GS

Proof of Concept Framework

Klaus Martiny (Deutsche Telekom)

Apr. 2018

RemarkDiscussion started in
May 2018

Approved to start at
the second meeting

GR: Group Report
GS: Group Specification[Preparation][Commissioning][Operation][Decommissioning]

Preparation of“template” fromwhich each
network slice
instance is derived

Creation of
network slice
instance basedon the template

Operation of
network slice
instances including
reallocation of
resources

Termination of
network slice
instance andrelease of theallocated resources

Fig. 1. Lifecycle management of network slice.

proposals were submitted. Among them, 18 contributions addressed scenarios and requirements, whichwere major topics at this meeting.
NTT submitted two contributions on network slice:
lifecycle management of network slice, and isolation
management. The basic concept of lifecycle management of network slice is defined in 3GPP (3rd Generation Partnership Project), a standards developing
organization for mobile communications systems. As
shown in Fig. 1, this concept consists of four phases:
preparation, in which a template is prepared to be
utilized to make network slice instances; commissioning, in which a network slice instance is produced
based on the template; operation, in which the slice
customer operates its own network slice instances
including reallocation of resources; and decommissioning, in which the network slice instance is terminated, and allocated resources are released.
NTT explained that all phases of lifecycle management of a network slice require complicated operations such as finding relevant resources, reserving theneeded amount of resources, and reallocating unused
resources. Although there was a general understanding on the use of ZSM in slice management among
the participants, the NTT contribution presented a
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Vol. 16 No. 9 Sept. 2018

clear rationale with detailed explanations. The proposal was accepted with minor updates based on theconstructive discussion.
Isolation is a key characteristic of network slice andrefers to the independence between network slice
instances. However, there has been no agreed formal
definition, and confusion has occasionally occurredin standardization discussions. The term isolation has
been used to describe the situation where no interference occurs between radio or optical signals in thefield of radio communications and optical transport.
In the initial stage of discussion of network slice, asuggestion was made to apply this well-establisheddefinition of isolation. However, ensuring complete
isolation, which is without any interference between
network slice instances, is too difficult to achieve dueto the characteristics of packet-based networks.
In view of this point, NTT proposed a new conceptof network slice isolation that is more realistic if ZSM
can successfully achieve certain capabilities. The
proposed network slice isolation is the situation
where negative impacts on network slice instancesfrom other overloaded network slice instances arelimited within the permissible level according to therequirements of the slice customer and its application
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Global Standardization Activities

Network slice instance A

Negative impact on network performance“Isolation” is maintained if
the negative impact on
network performance iswithin the permissible level.

Network slice instance B

Overloaded slice instanceFig. 2. Concept of isolation of network slice instances.

(Fig. 2).
This new concept drew attention from the participants and initiated some discussions. One of the discussions focused on how to handle a shared resourcesuch as PON (passive optical network) or CATV
(cable television) in the context of network slice isolation. In fact, the issue of resources shared among
different slice customers is one of the challenges in
network slice management, and substantial complexities are involved. NTT explained that ZSM
should target this challenge, and the proposed
approach was the starting point of this discussion.
Besides the NTT contributions, there were many
contributions that addressed network slice from different viewpoints. The momentum for network slice
discussion therefore increased during this meeting.
The term ZSM was used in the ZSM ISG as well as
in the preparation work without a clear definition.
The lack of a formal definition caused confusion during the discussion, and the meeting was therefore
suspended so the term could be clarified. To avoid
any further delays, the use of the “ZSM framework”
as the formal expression for the technology to be discussed in the ISG was agreed to in the second meeting. The NOC played an important role in establishing this formal definition of ZSM.
The architecture of ZSM will illustrate how theentire ZSM system is divided into sub-level components and will indicate functions within the system
and interworking with external functions/components. The architecture will be discussed after a set of
scenarios and requirements are identified. The participants in the second meeting discussed the architecture principles that will guide how the architecture
is illustrated. The concepts of modularity, extensibilNTT Technical Review

Vol. 16 No. 9 Sept. 2018

ity, scalability, model-driven, open interface, closed
loop management automation, security, authentication, and authorization were discussed and agreed.
The proof of concept (POC) is increasingly being
recognized as an important step in standardization
efforts. ZSM ISG is also undertaking the standardization of POCs to promote further standardization
activity and to encourage implementation of the produced specifications. The guidelines and generalprocedure of POCs were discussed in the second
meeting. A POC in ZSM is expected to follow current
best practices such as having a POC team consistingof more than two vendors and one telecom operator,
as already established in NFV and multi-access edge
computing.
4. Future plan
Subsequent meetings have been regularly held via
computer since the second meeting. The meeting frequency was reduced from weekly to every two weeks,
but the discussions have been so active that some
contributions have had to be carried over to the next
discussion due to a lack of time.
The third meeting was held in Shenzhen, China, inJune 2018, and the fourth meeting will be held in
Kansas in the United States in October 2018. The current Work Items will be concluded by the end of thisyear. At that time, ZSM ISG will reveal how ZSM
will achieve automation of network operation andhow this technology will help the business operationsof telecom operators.

42

Global Standardization Activities

Reference[1]

Zero-touch Network and Service Management – Introductory White
Paper,
https://portal.etsi.org/TBSiteMap/ZSM/OperatorWhitePaper

Trademark notes

All brand names, product names, and company names that appear in thisarticle are trademarks or registered trademarks of their respective owners.

Yoshinori Goto

Senior Research Engineer, Network Technology Project, NTT Network Technology Laboratories.
He received a B.E. and M.E. in applied physics
from Tohoku University, Miyagi, in 1992 and1994. He joined NTT Basic Research Laboratories in 1994. He has been researching and developing cable television systems, Internet protocol
television (IPTV), and machine-to-machine technology. He has been engaged in standardization
work for IPTV in the International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) as a member of the IPTV
Focus Group and Global Standards Initiative
since 2006. He has also served as Rapporteur of
Question 11 of ITU-T Study Group (SG)9, Questions 5 and 25 of ITU-T SG13, and Question 21
of ITU-T SG16. He has been a Vice-Chair of
ITU-T SG13 since 2013. He is a member of theInstitute of Electronics, Information and Communication Engineers.

NTT Technical Review

Vol. 16 No. 9 Sept. 201843

Short Reports

Completely Rewriting Industry’s
Understanding of Transmitting High
Quality Laser Processing Light overLong Distances

1. Introduction

2. Summary of achievements

NTT and Mitsubishi Heavy Industries, Ltd. (MHI)
entered into a cooperative agreement in April 2014 toundertake projects with the goal of creating newvalue for each other and their customers by applying
NTT’s research and development results in the area of
information and communication technology to
MHI’s social infrastructure products in fields such asenergy, the environment, and transportation, and toplant sites in Japan and other countries [1].
NTT and MHI have demonstrated kilowatt-class,high power single-mode laser transmission over several dozen to several hundred meters by harmonizing
NTT’s photonic crystal fiber (PCF) technology and
MHI’s high power laser processing technology. The
maximum transmission distance of over-1-kW single-mode laser light is limited to around only 10 m atpresent. Our achievement therefore makes it possible
to transmit high power single-mode laser light much
longer distances, that is, up to several dozen times
farther than before.
Laser processing technology is being used in various social infrastructure products, including vehicles
and airplanes, as an efficient method for cutting, holeforming, welding, and other processes, and its application field is expected to increase further. Ourachievement enables us to transmit high power single-mode laser light for distances greater than was
thought possible, while retaining the light’s quality,
to yield high accuracy laser processing sources. Consequently, this will be a key technology for accelerating the expansion in the application areas of laser
processing technology and for fostering further innovation in social infrastructure products.

In this achievement, NTT and MHI overcame thelimitations in transmission optical power and distance by employing PCF and achieved superior highpower transmission performance and feasible opticalfiber manufacturability simultaneously by proposing
a novel cross-sectional hole arrangement.
These key advances enable us to design a PCF withhigh power transmission potential four times higher
than that of existing single-mode fiber for high power
single-mode laser transmission. Moreover, NTT and
MHI successfully demonstrated 10-kW transmission
over 30 m and 1-kW transmission over 300 m using ahigh power single-mode laser light source and a fabricated PCF. This achievement expands the application area of high power single-mode laser processing
and is expected to dramatically advance manufacturing technology in various social infrastructure industries.

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Vol. 16 No. 9 Sept. 2018

3. Details of achievements
In this section, the PCF is described in more detail,and the results of experiments we conducted are
explained.
3.1 R
 eason for deployment of PCF (features of
PCF)
The optical fiber used to deliver the light from highpower single-mode laser to arbitrary processing sites
must offer high output power and excellent beam
quality. However, the optical power and distance inan optical fiber are limited by optical nonlinearity.
The maximum transmissible optical power and output beam quality of an optical fiber can be improved
44

Short Reports

Refractive index profile suitable for high power single-mode laser transmission

Material doped core

Cladding

Expanded core
Lower index difference
2nd cladding

Refractive index
difference
0.1–1%

Suitable for high power single-modelaser transmission
Impossible with material doping
Higher-ordermode lightSingle-mode
light
2nd cladding

Refractive index difference in PCF can be tailored to 0.01–10% by using number and diameter of air holes.

Control by
diameter

Control by
numberImage of refractive index profile control by air holes

Fig. 1. Basic concept for improving the high power transmission potential in an optical fiber and the applicability of PCF.

by various means, as follows:•	Expanding the core area, as it acts as the opticallight path•	Reducing the refractive index difference between
the core and cladding•	Filtering unwanted light propagation components (higher-order mode light) to maintain processing accuracy
However, these requirements demand extremely
precise refractive index control, on the order of
0.01%, which is impossible with conventional opticalfiber as it has a material doped core.
The PCF, on the other hand, confines the light to aregion surrounded by an array of air holes. The effective refractive index of the air hole array can be set
arbitrarily by altering the diameter d and number(alternatively, pitch Λ) of the air holes. Thus, thecross-sectional refractive index of a PCF can be
designed precisely to the order of 0.01–10%. This
superior control of the refractive index enables us toachieve single-mode transmission at arbitrary wavelengths.
NTT has successfully developed a low loss PCF for
realizing large capacity transmission at arbitrary
wavelengths. Moreover, NTT created an optical fiber
cord that can be used even if bent at 180 degrees without any optical signal degradation by combining thestrong confinement effect of air holes with convenNTT Technical Review

Vol. 16 No. 9 Sept. 2018tional optical fiber. As a result, NTT and MHI havesucceeded in transmitting high power single-modelaser light to remote processing sites with no quality
degradation by employing the superior refractive
index control offered by the PCF (Fig. 1).
3.2 N
 ovel quasi-uniform PCF and its optimization
As mentioned above, the transmission properties of
the PCF can be precisely controlled by setting thediameter d and pitch Λ of air holes. Further improvement is possible by combining multiple d and Λ values to design the cross-sectional air hole arrangement. However, the complex cross-sectional design
severely degrades the manufacturability of opticalfiber. To eliminate this problem, we developed for the
first time a quasi-uniform PCF; it has a constant d, butΛ varies. This enables us to expand the effective corearea while ensuring feasible levels of manufacturability. Moreover, we numerically clarified that by optimizing the values of d and Λ, the proposed quasiuniform PCF can achieve 420-kW•m high power
single-mode transmission. Power at this level is fourtimes higher than that of existing optical fiber.
3.3 H
 igh power single-mode transmission experiments
A 30-m-long quasi-uniform PCF was fabricated45Short Reports

based on the design guidelines. The output of a
10-kW single-mode laser light source was successfully transmitted over 30 m, and experiments confirmed its high power transmission potential of 270
kW•m. Similarly, a 1-kW single-mode laser light wastransmitted over 300 m, which corresponds to thehigh power transmission potential of 300 kW•m.
4. Future prospects
The achievements described here have enabled us
to expand the transmission distance of high power
single-mode laser light from several meters to several
hundreds of meters. Such performance surpasses thelimits currently deemed inevitable in the laser processing field and thus improves the effective use ofhigh power single-mode laser sources. The application of single-mode lasers not only improves the cutting and hole-forming accuracy but also reduces
processing time by using the laser energy more effectively.

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Vol. 16 No. 9 Sept. 2018

This achievement can be used to implement remote
processing, remote welding, and thick plate cutting in
the existing manufacturing processes of vehicles,
airplanes, marine vessels, and other products. This
achievement is expected to trigger rapid expansion in
the application area of laser processing technology toan extremely wide variety of social infrastructure
products, and to lead to greater innovations in manufacturing.
Reference[1]

Press release issued by NTT and MHI, “NTT and MHI Conclude Tieup Agreement in R&D Integrating Social Infrastructure and ICT,”
Apr. 24, 2014.
http://www.ntt.co.jp/news2014/1404e/140428a.html

For Inquiries
Public Relations, Planning Department,
NTT Information Network Laboratory Group
http://www.ntt.co.jp/news2018/1804e/180425a.html

46External Awards
ITU-AJ Encouragement Award
Winner: Junichi Iwatani, NTT Access Network Service Systems
Laboratories
Date: May 17, 2018
Organization: The ITU Association of Japan (ITU-AJ)
For his contribution to international standardization of the nextgeneration wireless local area network (LAN) IEEE 802.11ax andefforts to expand outdoor use of 5-GHz-band wireless LANs.
Best Paper Award
Winner: Tatsuhiko Iwakuni, Kazuki Maruta, Atsushi Ohta, Yushi
Shirato, Takuto Arai, and Masataka Iizuka, NTT Access Network
Service Systems Laboratories
Date: June 7, 2018
Organization: The Institute of Electronics, Information and Communication Engineers (IEICE)
For “Null-space Expansion for Multiuser Massive MIMO Interuser Interference Suppression in Time Varying Channels.”
Published as: T. Iwakuni, K. Maruta, A. Ohta, Y. Shirato, T. Arai, andM. Iizuka, “Null-space Expansion for Multiuser Massive MIMOInter-user Interference Suppression in Time Varying Channels,”
IEICE Trans. Commun., Vol. E100.B, No. 5, pp. 865–873, 2017.
TTC Information and Communication Technology Award,
Minister of Internal Affairs and Communications Prize
Winner: Eikazu Niwano, NTT Secure Platform Laboratories
Date: June 14, 2018
Organization: The Telecommunication Technology Committee(TTC)
For his contribution to research and development, international
standardization, and practical application of an IC (integrated circuit)card management system.

NTT Technical Review

Vol. 16 No. 9 Sept. 2018

Cannes Lions 2018
Bronze Lion - Design Lions (Environment & Experience Live Events)
Winner: Shingo Kinoshita and Takashi Miyatake, NTT Service
Evolution Laboratories; Junji Watanabe, NTT Communication Science Laboratories; Akira Ono, Tetsuya Yamaguchi, Koji Namba,
Koichi Furukado, Kiyoshi Tanaka, Katsumi Tanaka, Hikaru Takenaka, and Takuya Iwami, NTT Service Evolution Laboratories; Kazunari Moriuchi and Soichiro Usui, NTT Research and Development
Planning Department
Date: June 19, 2018
Organization: International Advertising Festival Limited
For “REDEFINING DISTANCE.”
The next-generation “5G” service will be put into practical use in2020 by NTT DOCOMO. This experimental project demonstrates
the speed, capacity, and low latency of 5G technology. It was performed by “Perfume,” the group that is always on the leading edge oftechnopop. The members have always performed together on thestage since forming the group. For the first time in 17 years, however,
the three women performed simultaneously on different stages inTokyo, New York, and London in this event. The communications
technology connected the three locations that are more than 10,000
km apart and combined the three respective performances into one
without any time lag.
Young Engineer’s Award
Winner: Azusa Ishii, NTT Device Innovation Center
Date: July 6, 2018
Organization: Japan Association of Corrosion Control
For “Comparison of Degradation Behavior of Poly(ethylene terephthalate) between Xenon-arc Accelerated Weathering and Outdoor
Exposure Tests” (in Japanese).
Published as: A. Ishii, T. Miwa, and H. Koizumi, “Comparison of
Degradation Behavior of Poly(ethylene terephthalate) between
Xenon-arc Accelerated Weathering and Outdoor Exposure Tests,”
Proc. of the 38th Bosei Boshoku Gijutsu Happyo Taikai (Rust Prevention and Control Technology Conference), pp. 121–126, Tokyo,
Japan, July 2018.

47

Papers Published in Technical Journals andConference Proceedings
Resource-efficient Verification of Quantum Computing
Using Serfling’s BoundY. Takeuchi, A. Mantri, T. Morimae, A. Mizutani, and J. F. FitzsimonsarXiv:1806.09138 [quant-ph], June 2018.
Verifying quantum states is central to certifying the correct operation of various quantum information processing tasks. In particular,
in measurement-based quantum computing, checking whether correct graph states are generated or not is essential for reliable quantum
computing. Several verification protocols for graph states have been
proposed, but none of these are particularly resource efficient: Many
copies are required in order to extract a single state that is guaranteed
to be close to the ideal graph state. For example, the best protocol
currently known requires O(n15) copies of the state, where n is thesize of the graph state. In this paper, we construct a significantly moreresource-efficient verification protocol for graph states that needs
only O(n5 log n) copies. The key idea that achieves such a drastic
improvement is to employ Serfling’s bound, which is a probability
inequality in classical statistics. Utilizing Serfling’s bound alsoenables us to generalize our protocol for qudit and continuous-variable graph states. The flexibility of Serfling’s bound also makes our
protocol robust; our protocol accepts slightly noisy but still usefulgraph states, which are rejected by previous protocols.

Haptic Interface Technologies Using Perceptual Illusions
T. Amemiya
Proc. of HCI International Conference 2018, pp. 168–174, Las
Vegas, USA, July 2018.
With virtual reality now accessible to anyone through high-end
consumer headsets and input devices, researchers are seeking costeffective designs based on human perceptual properties for virtual
reality interfaces. The author has been studying a sensory-illusionbased approach to designing human-computer interface technologies. This paper overviews how we are using this approach to develop
force displays that elicit illusory continuous force sensations by presenting asymmetric vibrations and kinesthetic displays based on across-modal effect among visual, auditory, and tactile cues of selfmotion.

Vestibular Display for Walking Sensation in a VirtualSpace
K. Shimizu, Y. Ikei, T. Amemiya, K. Hirota, and M. Kitazaki
Proc. of HCI International Conference 2018, pp. 334–339, Las
Vegas, USA, July 2018.

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Vol. 16 No. 9 Sept. 2018

This paper describes characteristics of walking sensation createdby a vestibular display (a motion seat). An active input was introduced to a passive presentation of a walking stimulus. The participant
triggered one step motion repeatedly by a game-controller button to
introduce agency of motion. First, the magnitude of the seat motion
was optimized to increase the walking sensation. Then, passive andpartially active seat motion was evaluated. As a result, it was shownthat added activity increased the walking sensation.

Airflow for Body Motion Virtual Reality
M. Kurosawa, Y. Ikei, Y. Suzuki, T. Amemiya, K. Hirota, and M.
KitazakiProc. of HCI International Conference 2018, pp. 395–402, Las
Vegas, USA, July 2018.
The present study investigates the characteristics of cutaneous
sensation evoked by airflow to the face of the seated and standinguser during the real and virtual walking motion. The effect of airflow
on enhancement of a virtual reality walk was demonstrated. The
stimulus condition provided in the evaluation involved the airflow,
the visual, and the vestibular presentations, and the treadmill andwalk-in-place real motions. The result suggested that the cutaneous
sensation of air flow was suppressed while the movement was performed actively with visual information provided. The equivalent
speed of air flow for the participants was 5–29% lower than the air
flow speed in the real walk.

Natural Language Inference with Definition Embedding
Considering Context on the Fly
K. Nishida, K. Nishida, H. Asano, and J. Tomita
Proc. of the 3rd Workshop on Representation Learning for NLP,
pp. 1–6, Melbourne, Australia, July 2018.
Natural language inference (NLI) is one of the most importanttasks in NLP. In this study, we propose a novel method using word
dictionaries, which are pairs of a word and its definition, as external
knowledge. Our neural definition embedding mechanism encodes
input sentences with the definitions of each word of the sentences on
the fly. It can encode definitions of words considering the context of
the input sentences by using an attention mechanism. We evaluatedour method using WordNet as a dictionary and confirmed that it performed better than baseline models when using the full or a subset of
100d GloVe as word embeddings.

48