EXHIBIT A

Case 6:20-cv-00454-ADA Document 1-1 Filed 06/02/20 Page 1 of 10
(12) United States Patent 

USOO736616OB2 

(10) Patent No.: US 7,366,160 B2 

Marily et al. (45) Date of Patent: Apr. 29, 2008 

(54) METHOD OF DETERMINING SERVICE 6,246,325 B1* 6/2001 Chittipeddi ................. 340,540 

TRENDS 6,272,110 B1* 8/2001 Tunnicliffe et al. ......... 370,232 

6,721,750 B1 * 4/2004 Jones et al. ................. 7O7/1OO 

(75) Inventors: Emmanuel Marily, Antony (FR); Stéphane Betge-Brezetz, Paris (FR): 

Olivier Martinot, Draveil (FR) FOREIGN PATENT DOCUMENTS 

(73) Assignee: Alcatel, Paris (FR) WO WO 0180492 A2 10, 2001 

(*) Notice: Subject to any disclaimer, the term of this 

patent is extended or adjusted under 35 OTHER PUBLICATIONS 

U.S.C. 154(b) by 1044 days. T. Volochine et al., “Network Management and Traffic Analysis for 

CICNET, IEEE Network, IEEE Inc., New York, US, vol. 5, No. 5 

(21) Appl. No.: 10/307,461 Sep. 1, 1991, pp. 41-50, XP000248472. 

(22) Filed: Dec. 2, 2002 * cited by examiner 

(65) Prior Publication Data Primary Examiner Melur Ramakrishnaiah 

US 2003/O108049 A1 Jun. 12, 2003 (74) Attorney, Agent, or Firm—Sughrue Mion, PLLC un. I Z, 

57 ABSTRACT (30) Foreign Application Priority Data (57) 

Dec. 3, 2001 (FR) ................................... O1 15584 The invention proposes a method of determining commu 

(51) Int. Cl nications network service trends. The invention therefore 

itoul i2/66 (2006.01) selects two or more parameters of a network representative of a network service and variable in time, measures at two 

(52) U.S. Cl. .........r 370/352; 370/395.21: 709/226 or more times values of the network parameters, determines 

(58) Field of Classification Search .no in 370/352, at two or more times the value of a service indicator as a 

370/230, 235, 395.2: 709,219, 232, 224, function of said measured parameter values, and determines 

709/228: 379/903, 112.01 a trend of the indicator as a function of said determined 

See application file for complete search history. indicator values. The method is used in particular to deter 

(56) References Cited mine a time remaining before a service violation or the crossing of a threshold. 

U.S. PATENT DOCUMENTS 

5,909,750 A * 6/1999 Sanders ....................... 139/11 12 Claims, 4 Drawing Sheets 

SELECTA PLURALITY OF 

NETWORK PARAMETERS 

REPRESENTATIVE OF A SERVICE 

MEASURE PARAMETERS 

AT ONE TIME 

MEASURE PARAMETERS 

AT ANOTHER TIME 

DETERMINEASERVICE TREND 

 

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U.S. Patent Apr. 29, 2008 Sheet 1 of 4 US 7,366,160 B2 

FIGL1 

START 

SELECT A PLURALITY OF 

NETWORK PARAMETERS 

REPRESENTATIVE OF A SERVICE 

MEASURE PARAMETERS 

AT ONE TIME 

MEASURE PARAMETERS 

AT ANOTHER TIME 

DETERMINE A SERVICE TREND 

 

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U.S. Patent Apr. 29, 2008 Sheet 2 of 4 US 7,366,160 B2 

 

Case 6:20-cv-00454-ADA Document 1-1 Filed 06/02/20 Page 4 of 10
U.S. Patent Apr. 29, 2008 Sheet 3 of 4 US 7,366,160 B2 

FG3 

MEASURE NETWORK PARAMETERS 

PO, P1, P2AT SEVERAL TIMES 

DETERMINE TRENDS TPO, TP1 

OF PARAMETERS P0, P1 

TS DETERMINED 

TS2 DETERMINED 

VOLATION 

AT ta. 

YES 

VIOLATION 

AT ta. 

NO 

NO 

 

 

 

 

 

 

 

 

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U.S. Patent Apr. 29, 2008 Sheet 4 of 4 US 7,366,160 B2 

FG-4 

5 9 

1, f. 

E 

10 

- 

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US 7,366,160 B2 

1. 

METHOD OF DETERMINING SERVICE 

TRENDS 

The invention relates to network monitoring methods, and 

more particularly to methods of determining service trends 

in a telecommunications network. 

BACKGROUND OF THE INVENTION 

BMC Software’s “Patrol Dashboard” product uses a net 

work monitoring method which measures the bandwidth of a network at different times and determines a bandwidth 

trend as a function of the measurements. 

Patent application WO 01/80492 discloses a service qual ity indicator monitoring technique for use in telecommuni 

cations networks. However, monitoring is based on a Sub 

jective indicator and not on a trend calculation. 

Consequently, the variation over time of the monitored 

indicator cannot be determined. 

In service level agreements (SLAs) between a network 

service provider and a user, the service provider undertakes 

to provide a network service with a given failure level. The 

network service may consist in real time transfer of sound or 

pictures, for example. At present there are no tools for 

forecasting accurately the failure of a network service. 

OBJECTS AND SUMMARY OF THE 

INVENTION 

Thus there is a need for a method that solves this problem. 

The invention therefore proposes a method of determining 

communications network service trends, the method com 

prising the steps of 

Selecting two or more parameters of a network represen 

tative of a network service and variable in time; 

measuring and/or calculating at two or more times values 

of the network parameters; 

determining at two or more times the value of a service 

indicator as a function of said measured and/or calcu 

lated parameter values; and 

determining a trend of the indicator as a function of said 

determined indicator values. 

In one implementation, the method further comprises a 

Subsequent step of determining as a function of the trend of 

the indicator a time of the service indicator crossing a 

defined threshold. 

In another implementation the network service is selected 

from the group comprising: Voice; Videophone; telephone; 

multimedia; video on demand; private virtual network; real 

time data; interactive data; and data stream services. 

In a further implementation the method further comprises 

a step of determining an indicator plane by linear regression 

of the measured and/or calculated network parameters. 

In a still further implementation determining the service 

trend includes comparing parameter values with predeter 

mined thresholds. 

Determining the service trend may further comprise: 

determining a network parameter trend; and 

comparing the parameter trend with a predetermined 

threshold. 

In one implementation the trend of the indicator is deter 

mined by a neural network. 

In another implementation the method further comprises 

a training step in which the neural network determines rules 

of association between a service trend and service parameter 

values. 

5 

10 

15 

25 

30 

35 

40 

50 

55 

60 

65 

2 

In a further implementation the training step comprises 

inserting into the neural network a training base providing 

service trend values associated with service parameter val CS. 

In a still further implementation the neural network is a 

multilayer network. 

The method may further comprise a step of calculating a 

mathematical expectation of financial loss as a function of 

the network service trend determined. 

In one implementation the method further comprises a 

step of determining a capacity to provide a network service 

at a given time. 

The invention further provides a network and/or service 

management system using the above method. 

Thus the invention indicates a trend of the measured 

indicator, unlike the above-mentioned patent application 

WO 01/80492, for example. The trend can show whether the 

indicator is likely to cross a defined threshold or even 

determine when it will cross the threshold. In one imple mentation of the invention, a reliability criterion may also be 

determined for the estimated threshold crossing time. 

BRIEF DESCRIPTION OF THE DRAWINGS 

Other features and advantages of the invention become 

apparent on reading the following description of implemen 

tations of the invention, given by way of example and with 

reference to the drawings, in which: 

FIG. 1 shows an algorithm of a simplified example of a 

method in accordance with the invention for determining 

network service trends; 

FIG. 2 shows a first implementation of a method of 

determining network service trends; 

FIG. 3 shows a simplified algorithm of a second imple 

mentation of the invention; and 

FIG. 4 is a diagram of a neural network used in a third 

implementation of the invention. 

MORE DETAILED DESCRIPTION 

The invention proposes a method of determining service 

trends. To this end various network parameters representa 

tive of a service are selected, after which a network service 

trend is determined as a function of those parameters. 

FIG. 1 shows a simplified algorithm of one example of a 

method of the invention for determining service trends. In a 

first step of the method, a plurality of network transmission 

parameters that are representative of a network service is 

selected. In a second step, the values of the selected param 

eters at a given time are measured or calculated. In a third 

step, the values of the parameters at another time are 

measured or calculated. In a fourth step, a service trend at 

the later time is determined from the measured parameters. Various types of parameter measured as a function of 

different network services are described below. Examples of 

trend determination are also described below. 

A level of service indicator can be defined on the basis of 

measured and/or calculated data. The value of the indicator 

at different times can be used to determine the service trend. 

One or more trends extrapolated from measurements of a 

parameter can also be used in the definition of the indicator. 

At a given time the indicator can also be defined by the 

values of different parameters at different times. 

In this way a number of network parameters, also known 

as service level specifications (SLSs), can be identified for 

preferential observation in order to determine the level of 

service. These parameters include in particular: packet 

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US 7,366,160 B2 

3 

losses; time-delays between packets; jitter or stability; band 

width: bandwidth stability; and the directionality of the 

communication. Parameters that have been calculated or 

extrapolated from measurements can therefore be used. For 

example, bandwidth stability changes can be calculated and 

used in determining the network service indicator. Param 

eters of this kind enable the reliability of the network service 

to be determined, for example. Extrapolated parameters can 

also be used, for example trends of the parameters previ 

ously identified. 

The service level can relate to any type of network 

service. The following services may nevertheless be high lighted: Voice transfer services; telephone services; video 

phone services; multimedia transfer services; video on 

demand services; whiteboard application services; virtual 

private network services; real time data transfer services; 

and interactive data transfer services. These service can in 

particular be used for transmission services conforming to 

the Internet Protocol (IP). 

A plurality of network parameters can be selected to 

define the level of service as a function of the service or 

group of services concerned. The parameters can be 

weighted as a function of their importance for a given level 

of service. Weighting gives dominant importance to the most 

sensitive parameters in determining a given network service 

trend. The table below sets out one example of association 

and weighting between a network service and network 

parameters. 

The values in the table indicate the weighting or sensi 

tivity of each parameter, from 0 for the minimum weighting 

to 3 for the maximum weighting. 

Packet Time- Band- Direction 

loss delay Jitter width ality 

Voice 1 3 3 2 2 

Videophone 1 3 2 3 2 

Telephone 1 1 O O 1 

Multimedia 2 3 O 3 1.5 

Video on demand 1 3 O 3 1 

Whiteboard 3 2 O O 2 

Virtual private network 2 

Real time data 3 3 O 2 2 

Interactive data 3 2 O O 1 

Data streams 3 1 O O 1 

Services can also be grouped into categories of services. 

The 3GPP and Tequila projects define categories of services 

and of parameters that are to be accorded preference for the 

categories concerned. The invention proposes to associate 

categories of services with network parameters. The table 

below sets out one example of the weighting of network 

parameters associated with different categories. 

Band- Packet Time 

Service category width loss delay Jitter 

Interactive use: 1 2 3 1 

Telnet, database access, short 

Internet transactions, Xwindow, etc. 

Interactive multimedia use: 2 2 3 3 

Voice or video over IP, etc. 

Non-interactive multimedia use: 3 2 1 1 

Remote training, broadcasting, etc. 

5 

10 

15 

25 

30 

35 

40 

45 

50 

55 

60 

65 

-continued 

Band- Packet Time 

Service category width loss delay Jitter 

Request-oriented use: 2 1 3 1 

Client Server, etc. 

Transfer use: 3 1 1 1 

FTP, back-ups, telesales, long 

Internet transactions, etc. 

In a first implementation, shown in FIG. 2, a level of 

service indicator is defined by a geometrical shape, in this 

example by a plane 1. The measured parameters are repre 

sented along three axes defining a three-dimensional space, 

for example an axis X representing time, an axis y for the 

parameter values, and an axis Z representing the parameters 

Po, P and P. 

An indicator plane 1 can be defined from the values of the 

parameters in this space. For example, the indicator plane 

can be obtained by linear regression of the values of the 

parameters P, P and P. in a given time interval preceding 

the time at which the trend is to be determined. For example, the basic principles of spatial-temporal filtering methods that 

transform the detection of movement in two spatial dimen 

sions into a problem of estimating the orientation of a plane 

can be used (see Adelson E. H., Bergen J. R. “Spatiotem 

poral energy models for the perception of motion”. J. Optical 

Society of America, vol. A2, no.2, pp. 284-299, 1985 and 

Laplante P. A., Stoyenko A. D., “Real time imaging theory, technique and application', IEEE Press 1996. The plane is 

in itself a service trend indicator. 

The parameters represented in the space can be trans 

formed in various ways. Thus a multiplier coefficient can be 

applied to values of a parameter so that the parameter values 

have comparable amplitudes. A parameter whose trend is 

generally the opposite of that of the other parameters can be 

inverted. A weighting as defined previously can also be used 

to establish the equation of the indicator plane. For example, weighted regression methods with a priori weights or with 

weights that are a function of the residues can be used. 

Another trend indicator can also be extrapolated from the 

plane defined above. For example, a trend vector 4 can be 

defined having coordinates (x, y, o) in the indicator plane. The vector provides a simplified indicator representative of 

the service trend. Another trend indicator can be extrapo lated from the plane 1. For example, this indicator can be the 

slope of a straight line segment defined by the intersection 

of the indicator plane and a reference plane with the equation 

Z=O. 

These trend indicators are used to define service evolution 

forecasts, for example. It is therefore possible to establish a 

time remaining up to a threshold crossing, a level of service 

after a predetermined time period, a service provision capac 

ity before failure, or a mathematical expectation of loss as a 

function of the applicable service agreement. 

Provision can be made for generating a signal to warn of 

a predetermined trend being exceeded, for example a visual 

or an audible signal. A trend having a high slope may be 

synonymous with imminent failure of the network service, 

and this kind of signal can enable appropriate preventive 

measures to be implemented. This form of trend determi 

nation also enables the evolution requirements of the net 

work in the short, medium and long term to be determined. 

Thus the duration of the measurements used to determine the 

trend as a function of the term to beforecast can be modified. 

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5 

An example of service level threshold crossing forecast 

ing is given first. In FIG. 2, for example, a service threshold 

geometrical Surface Such as a plane 2 can be defined. A curve 

3 can then be determined at the intersection between the 

indicator plane 1 and the threshold geometrical Surface or 

plane 2. For parameters represented with values from 0 to N 

along the Z axis, a time remaining can then be determined 

from the portion of the intersection curve whose values of Z 

are from 0 to N. The average value of the time of the curve 

portion or one of its extreme values for Z from 0 to N can be 

used. The lower time value T of the curve portion can thus 

be used to supply the least favorable threshold crossing hypothesis. 

Although both a reference geometrical element 2 and an 

indicator geometrical element 1 are described above as 

being in the form of planes, any appropriate geometrical 

shape can be used to extrapolate a trend. 

Service trend forecasting can also be used to calculate the 

mathematical expectation of financial loss. An SLA can 

specify that the network service provider must pay the user 

an indemnity. A loss at a given time can then be determined as a function of the terms and conditions of the SLA. 

Network service priorities can therefore be forecast as a 

function of loss expectations calculated for different SLA. 

Trend determination can also be used to determine the 

service provision capacity at a given date. If the level of 

service is forecast at a given level at a given time, a service 

provision capacity at that time can be determined. A capacity 

to enter into service level agreements before reaching a 

saturation service level can therefore be defined. 

These forms of service trend determination can also be 

used in conjunction with other methods of determining 

trends, a few examples of which are given below. 

A second implementation of the method of determining 

the service level trend, shown in FIG. 3, analyses specific instances of a plurality of network parameters to determine 

a trend. In this implementation, various network parameters 

are compared with predetermined threshold logic levels. 

Boolean criteria can be applied to the parameter values for 

this purpose. A predetermined service trend is then associ 

ated with a combination of parameter levels. This method 

can include a preliminary step of measuring network param 

eters and associating the parameters with network service 

trends. This implementation is particularly appropriate for 

detecting a trend as a function of practical situations noted 

by a network operator. In the FIG. 3 example, the trends TP 

and TP of the parameters Po and P are determined before 

hand. These trends are then used to determine the network 

service trends TS or TS. Network parameter values are 

also used to determine the network service trend. The trends 

determined can be used for the forecasts previously described. Thus there can be a step of forecasting the 

network service violation time. To determine the service 

violation time for a particular service trend, account is taken 

of the time at which the service trend was calculated, for 

example. 

Another implementation is particularly suitable for deter 

mining network service trends in which the evolution of the 

measured or calculated parameters is non-linear. In this 

implementation, a neural network is used to determine the 

network service trend. FIG. 4 shows an example of a neural 

network used in the context of the invention. A multilayer 

neural network 10 is used, i.e. a network having one or more 

input layers 5, a hidden intermediate layer 9, and an output 

layer 11. An input layer 5 having N input neurons, a hidden 

5 

10 

15 

25 

30 

35 

40 

45 

50 

55 

60 

65 

6 

layer 9 having 2N+1 neurons and an output layer 11 having 

a number of outputs chosen by the user are used, for 

example. 

Values of network parameters 6 and/or trends 7 of those 

parameters are applied to the input neurons 5. Threshold 

values 8 of the parameters SLS can also be applied to the 

input neurons 5. The values 6, 7 and 8 applied at the input 

are then processed in the hidden layer 9. The output layer 

then Supplies a number of defined signals 12. The signals 12 

can indicate different crossings, for example a warning 

signal can therefore be provided, such as: a trend threshold 

crossing warning signal; a time remaining before a service 

violation threshold crossing warning signal; or any other 

appropriate warning signal to warn the network operator of 

how the service is changing. 

Use of a neural network can comprise a plurality of steps. 

In a first time period, a training base is formed, based on 

experimental results, for example. The training base com 

prises a multitude of output neuron states as a function of 

input neuron states. During a training step, the training base 

is integrated into the neural network. The training step 

consists of determining the weights of the neural connec 

tions of the neural network using training rules. Error 

gradient backpropagation rules can be used. This method is 

known in the art and consists in weighting the links between 

the neurons and recurrently correcting the weightings. Thus 

the result obtained with a test weighting is compared with a 

result fixed previously in the training base. The recurrent 

process is interrupted when the error in respect of the output 

neurons is below a predetermined threshold. Neural network 

software is available, for example the Stuttgart Neural 

Network Simulator. The neural network can also be imple mented in the form of an integrated circuit. The person 

skilled in the art knows how to choose an appropriate number of hidden layers as a function of the complexity of 

the network service to be monitored. 

Using a neural network is more rugged or resistant to error 

or uncertainty in respect of one or more parameters and also 

enables non-linear or cyclic behaviors to be observed. 

The implementations described by way of example herein 

are offered by way of illustrative and non-limiting example, 

and the invention is not limited to the details given here, but 

can be modified within the scope of the accompanying 

claims. 

What is claimed is: 

1. A method of determining communications network 

service trends, the method comprising the steps of: 

selecting two or more parameters of a network represen 

tative of a network service and variable in time; 

measuring and/or calculating at two or more times values 

of the network parameters; 

determining at two or more times the value of a service 

indicator as a function of said measured and/or calcu 

lated parameter values; 

determining a trend of the indicator as a function of said 

determined indicator values, and 

determining as a function of the trend of the indicator a 

time of the service indicator crossing a defined thresh 

old. 

2. The method of claim 1, wherein the network service is 

selected from the group comprising: Voice; videophone; 

telephone; multimedia: Video on demand; private virtual 

network; real time data; interactive data; and data stream 

services. 

3. The method of claim 1, further comprising a step of 

determining an indicator plane by linear regression of the 

measured and/or calculated network parameters. 

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7 

4. The method of claim 1, wherein the determining the 

service trend includes comparing parameter values to pre 

determined thresholds. 

5. The method of claim 4, wherein the determining the 

service trend further comprises: 

determining a network parameter trend, and 

comparing the parameter trend to a predetermined thresh 

old. 

6. The method of claim 1, wherein the trend of the 10 

indicator is determined by a neural network. 

7. The method of claim 6, further comprising a training 

step in which the neural network determines rules of asso 

ciation between a service trend and service parameter val CS. 

5 

8 

8. The method of claim 7, wherein the training step comprises inserting into the neural network a training base 

providing service trend values associated with service 

parameter values. 

9. The method of claim 8, wherein the neural network is 

a multilayer network. 

10. The method of claim 1, further comprising a step of 

calculating a mathematical expectation of financial loss as a 

function of the network service trend determined. 

11. The method of claim 1, further comprising a step of 

determining a capacity to provide a network service at a 

given time. 

12. A network and/or service management system using a 

method according to claim 1. 

k k k k k 

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