APPLYING INTEGRATED EXPERT SYSTEM

IN NETWORK MANAGEMENT

Antonio Martín, Carlos León, Juan I. Guerrero and Francisco J. Molina

Dpto. Tecnología Electrónica, Universidad de Sevilla, Avda. Reina Mercedes s/n., Sevilla, Spain

Keywords: Expert System, TMN, GDMO, Knowledge Representation, Management Information Base.

Abstract: The management of modern telecommunications networks is becoming an increasingly demanding task that

is difficult to implement using present traditional methods even assisted by conventional automation

techniques. Integration of advanced Artificial Intelligence (AI) technology into existing and future network

management system may resolve some of the difficulties. The goal of this research is to develop an

integrated expert system for management network applications. The emphasis of this research is to provide

a broad view of intelligent systems by capturing the knowledge of human experts and using a modular

approach that integrates the knowledge management and network resources specifications. For this purpose,

an extension of OSI management framework specifications language has been added and investigated. The

advantage of integrating both is that a large problem can be broken down into smaller and manageable sub-

problems/modules. Through modification of existing resources or addition of new resources, the integrated

expert system can be conveniently expanded in the future to cover the latest research findings and updated

standards of network communications.

1 INTRODUCTION

Current communications networks support a large

demand of services for which the traditional model

of network management is inadequate. The network

management has evolved: local systems with

autonomous administration, heterogeneous

management and integrated management. The

traditional expert management uses management

knowledge and management information separately.

It is necessary to develop new models, which offer

more possibilities. We propose a new evolution

called Integrated Management Expert Systems.

We propose a technique which integrates the

Expert System completely within the Management

Information Base (MIB) (Morris, 2003). Integrating

both elements is the main purpose of our work. This

task is achieved by integrating knowledge base of

expert system within the management information

used to manage a network. For this purpose, an

extension of OSI management framework

specifications language has been added and

investigated in this study. A new property named

RULE has also been added, which gathers important

aspects of the facts and the knowledge base of the

embedded expert system.

By integrating the knowledge base in resources

specifications, expert system has the power to

provide diagnosis of fault network, which can assist

civil engineering trainees, inspectorate staff and

professional. The NOMOS+ is a prototype

implemented through this thesis as a system based

on integrated expert rules.

2 NETWORK MANAGEMENT

At the moment there are two main management

models: OSI and Internet. Both network

management systems operate using client/server

architecture. Four fundamental concepts of these

models are (Clemm, 2006):

- Manager or Manager Role: In the network

management model a manager is an unit that

provides information to users, issues requests to

devices in a network, receives responses to the

requests and receives notifications.

- Agent or Agent Role: An agent is an unit that is

part of a device in the network that monitors and

maintains status about that device. It can act and

respond to requests from a manager.

- Network Management Protocols: Managers and

agents require some form of communication to issue

101

Martín A., León C., I. Guerrero J. and J. Molina F. (2007).

APPLYING INTEGRATED EXPERT SYSTEM IN NETWORK MANAGEMENT.

In Proceedings of the Ninth International Conference on Enterprise Information Systems - AIDSS, pages 101-106

DOI: 10.5220/0002361201010106

 SciTePress

their requests and responses. SNMP is the protocol

used to issue requests and receive responses in a

management model Internet. CMIP is the protocol

used in management model ISO.

- Management Information Base (MIB): In

addition to being able to pass information back and

forth, the manager and the agent need to agree on

and understand what information the manager and

agent receive in any exchange. This information

varies for each type of agent. The collection of this

information is referred to as the management

information base. A manager normally contains

management information describing each type of

agent the manager is capable of managing. This

information would typically include Internet MIB

definitions and ISO definitions for managed objects

and agents.

In the Open System Interconnection (OSI)

systems management the information architecture is

based on an object-oriented approach and the

agent/manager concepts that are of paramount

importance.

After this brief introduction to management

elements in common to OSI an Internet models, we

will approach our research in the integration of

knowledge management into MIB in the OSI

management model.

We are studying the way to integrate the expert

knowledge in the management Internet model.

Internet management model doesn’t use the Object

Oriented Programming such as it is used by the OSI

model. This is one of the reasons for the Internet

model simplicity. The definitions contain objects,

specified with ASN.1 macros.

The resources specifications can only be groups

of scalar variables and cells tables in spite of not

being an Object Oriented Programming model, we

can use the tables as classes where the attributes are

the table columns and every file contains an instance

of the class. The same as in OSI every object has an

OID associated identifier.

3 MANAGEMENT MODEL OSI

The description of management information has two

aspects. First, a Structure of Management

Information (SMI) defines the logical constitution of

management information and how it is identified and

described.

Second, the MIB, which is specified using the

SMI, defines the actual objects to be managed. The

MIB is a conceptual repository of management

information. It is an abstract view of all the objects

in the network than can be managed. In OSI, SMI

provides the Guidelines for Definition of Managed

Objects (GDMO), for definition objects contained in

the MIB (ISO, 1992).

A managed object is the OSI abstract view of a

logical or physical system resource to be managed.

These special elements provide the necessary

operations for the administration, monitoring and

control of the telecommunications network. The

managed objects are defined according to the

International Standardization Organization (ISO)

Guidelines for the Definition of Managed Objects

(GDMO), which defines how network objects and

their behaviour are to be specified, including the

syntax and semantics.

GDMO has been standardized by ITU

(International Telecommunication Union) in ITU-T

X.722 and is now widely used to specify interfaces

between different components of the TMN

(Telecommunication Management Network)

architecture (ITU-T, 1996).

GDMO is organized into templates, which are

standard formats used in the definition of a

particular aspect of the object. A complete object

definition is a combination of interrelated templates.

There are nine of these templates: class of managed

objects, package, attribute, group of attributes,

action, notification, parameter, connection of name

and behaviour.

4 STANDARD GDMO+

The elements that at the moment form the GDMO

standard do not make a reference to the knowledge

base of an expert system. To answer these questions,

it will be necessary to make changes on the template

of the GDMO standard. We present an extension of

the standard GDMO, to accommodate the intelligent

management requirements.

We describe how to achieve this goal using a

new extension called GDMO+. This extension

presents a new element RULE, which defines the

knowledge base of the management expert system.

This template groups the knowledge base supplied

by an expert in a specific management dominion. It

allows the storage of the management knowledge in

the definition of the resources that form the system

to be managed.

The standard that we propose contains the

singular template RULE and its relations to other

templates. Two relationships are essential for the

inclusion of knowledge in the component definition

of the network: Managed Object Class and Pack-

age template, Figure 1.

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In the standard we propose, both templates have

the new property RULES. Let us study both

relationships.

4.1 Managed Object Class Template

This template is used to define the different kinds of

objects that exist in the system. The definition of a

Managed Object Class is made uniformly in the

standard template. This way we ensure that the

classes and the management expert rules defined in

system A can be easily interpreted in system B.

<class-label> MANAGED OBJECT CLASS

[DERIVED FROM <class-label> [,<class-label>]*;]

[CHARACTERIZED BY <package-label>

[,<package-label]*;]

[CONDITIONAL PACKAGES

<package-label> PRESENT IF condition;

,<package-label>] PRESENT IF condition]*;]

REGISTERED AS object-identifier;

DERIVED FROM plays a very important role,

when determining the relations of inheritance which

makes it possible to reutilize specific characteristics

in other classes of managed objects.

This template can also contain packages and

conditional packages, including the clauses

CHARACTERIZED BY and CONDITIONAL

PACKAGES (Hebrawi, 1995).

4.2 Package Template

This template is used to define a package that

contains a combination of many characteristics of a

managed object class: behaviours, attributes, groups

of attributes, operations, notifications and

parameters. In addition to the properties indicated

above, we suggest the incorporation of a new

property called RULES, which contains all the

specifications of the knowledge base for the expert

system.

<package-label> PACKAGE

[BEHAVIOUR <behaviour-label>

[,<behaviour-label>]*;]

[ATTRIBUTES

<attribute-label>propertylist[,<parameter-label>]*

[,<attribute-label>propertylist[,<parameter-label>]*]*;]

[ACTIONS <action-label> [<parameter-label>]*

[<action-label> [<parameter-label>]*]* ;

[NOTIFICATIONS

<notification-label> [<parameter-label>]*

[<notification-label> [<parameter-label>]*]* ;]

[RULES <rule-label> [,<rule-label>]*;]

REGISTERED AS object-identifier;

All the properties that we define in the package

will be included later in the Managed Object Class

template, where the package is incorporated. A same

package can be referenced by more than one class of

managed objects.

The property RULES allows a treatment similar

to the other properties, including the possibility of

inheritance of rules between classes. Like the rest of

the other properties defined in a package, the

property RULES need a corresponding associated

template.

4.3 Expert Rule Template

Knowledge is represented in production rules or

simply rules. Rules are expressed as IF-THEN

statements which are relatively simple, very

powerful as well as very natural to represent expert

knowledge. A major feature of a rule-based system

is its modularity and modifiability which allows for

incremental improvement and fine tuning of the

system with virtually no degradation of

performance. The structure of the RULE template is

shown here:

<rule-label> RULE

[PRIORITY <priority>;]

[BEHAVIOUR <behaviour-label>[,<behaviour-label>]*;]

[IF occurred-event-pattern [,occurred-event-pattern]*]

[THEN sentence [, sentence]* ;]

REGISTERED AS object-identifier;

In our study case the template RULE permits the

normalized definition of the specifications of the

expert rule to which it is related. This template

allows a particular managed object class to have

properties that provide a normalized knowledge of a

management dominion.

The following elements compose a normalized

definition of an expert rule.

- <rule-label>: This is the name of the management

expert rule and RULE, a key word indicates the type

of template.

- BEHAVIOUR: This construct is used to extend

the semantics of previously defined templates.

Figure 1: Relations between proposed standar

templates.

APPLYING INTEGRATED EXPERT SYSTEM IN NETWORK MANAGEMENT

103

- PRIORITY: This represents the priority of the rule,

that is, the order in which competing rules will be

executed.

- IF: It contains all the events that must be true to

activate a rule. Those events must be defined in the

Notification template. We can add a logical

condition that will be applied on the events occurred

or their parameters.

- THEN: This gives details of the operations

performed when the rule is executed. Those

operations must be previously defined in the Action

template. These are actions and diagnoses that the

management platform makes as an answer to

network events occurred.

- REGISTERED AS is an object-identifier: A clause

identifies the location of the expert rule on the ISO

Registration Tree. The identifier is compulsory.

5 APPLICATION OF GDMO+

To show the viability of our proposal, we proceed to

the study and building of a management Expert

System, so that the corresponding knowledge base

begins to belong to the normalized proprieties

information defined by the managed resources. For

this we use an expert system developed for the

management of a data network belonging to an

electrical company. The definitions of the employed

resources and the expert knowledge base use an

unique specification. To define these specifications

we will use the syntax and rules investigated in

GDMO+ standard.

We present a rule-based expert system applied to

the fault diagnosis in telecommunication system of a

power utility. The communications systems

employed to implement the integrated intelligent

management prototype belongs to the SEVILLANA-

ENDESA (CSE) a major Spanish power utility. The

current management and control of that network is

based on an Expert System called NOMOS

developed by the Electronic Technology Department

in the University of Seville (Leon, 1999). Our tool

understands transceivers and multiplex equipment.

The knowledge base of this system is integrated

in the specifications of the resources using for that

purpose our GDMO+ proposal. These new

specifications contain management information of

managed resources and include also the set of expert

rules that provides the knowledge base of the expert

system.

5.1 Related Work

Part of SEVILLANA-ENDESA's long-distance

traffic is controlled by a wireless System distributed

throughout the CSE network. Expert systems are

part of the system dedicated to the management of a

power utility's communications system, which we

call NOMOS+ (Martin, 2006). It has been employed

a Sun Blade 150 Workstation to program the expert

system. The resultant expert system has about 200

rules. NOMOS+ is an extension for intelligent

decision-making and diagnostic reasoning controlled

by its own integrated expert system. NOMOS+ is the

first production software written and integrated in

GDMO+.

NOMOS+ is implemented in Brightware's

ART*Enterprise, an expert system shell. The

experience with NOMOS+ is that ART*Enterprise is

a useful tool for developing expert systems.

5.2 The System Features

NOMOS+ operations, uses a supervision system

called SSC (Communication Supervisory System).

Figure 2: Communication Supervisory System.

This system can monitor, in real time, the

network's main parameters, making use of the

information supplied by a Supervisory Control and

Data Acquisition (SCADA), formed by a Control

Centre (placed on the main CSE building), and

Remote Terminal Units (RTUs) installed into

different stations. The use of a SCADA system is

due to the management limitations of network

communication equipment.

The SSC allows the operator to acquire

information, alarms or digital and analogical

parameters of measure, registered on each RTU.

Starting from the supplied information, the operator

is able to undertake actions through the SSC in order

to solve the failures that could appear or to send a

technician to repair the stations equipment (Garcia,

2001).

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5.3 The System Architecture

Our tool has three major components:

- The inference engine: This is the processing unit

that solves any given problems by making logical

inferences on the given facts and rules stored in the

knowledge base. In our tool we used the

ART*Enterprise. By using an existing general

purpose tool we were able to build a standard and

extensible platform with proven performance and

quality.

- The knowledge base: This is a collection of expert

rules and facts expressed in the ARTScript

programming language ART*Enterprise.

The knowledge base contains both static and

dynamic information and knowledge about different

network resources and common failures. The

knowledge base of our system can be extended by

adding new higher level rules and facts. To this

purpose we can employ user interface.

- The user interface: This controls the inference

engine and manages system input and output. The

user interface of our tool contains a preprocessor for

parsing GDMO+ specification files, a set of input

and output handling routines for managing the

system. Also, the user interface components allow

administrators to inspect the definitions of

management object classes interactively. The user

interface allows to modify and to include new expert

management rules in the managed objects definition.

5.4 A Management Expert Rule

Next paragraph shows an example of expert rules

integration in the GDMO+ proposed standard. This

defines a Managed Objects Class:

radioTransceptorCTR190, which defines the

properties corresponding to the radio transceiver

devices. This class includes all the specifications

corresponding to the resource.

radioTrasnceptorCTR190 MANAGED OBJECT CLASS

DERIVED FROM “rec.X721”:top;

CHARACTERIZED BY transceptorPackage;

RULES powerErrorCTR190, linkCTR190

REGISTERED AS {nm-MobjectClass 1};

powerErrorCTR190 RULE

PRIORITY 3;

BEHAVIOUR powerErrorCTR190Behaviour;

IF (?date ? ?local 7_F_ALIM_2 ?remote ALARM)

THEN (“Severity:" PRIORITY),

(“Diagnostic: It damages in the electric feeding

of the station” ?local),

(“Recommendation:

To revise the electric connection”, ?local);

REGISTERED AS {nm-rule 1};

linkCTR190 RULE

PRIORITY 4;

BEHAVIOUR linkCTR190Behaviour;

IF (?date ?time1 ?local 7_TX_C2 ?remote ALARM

(?date ?time2 ?local 7_TX_C2 ?remote ALARM

& : (<(ABS(? ?time1 ?time2)) 1.00))

THEN (“Severity:" PRIORITY) ,

(“Diagnostic: “Mistake in transmission ”, ?local),

(“Recommendation “Revise transceiver”);

REGISTERED AS {nm-rule 2);

The most important properties that we can

indicate are the two expert rules that have been

associated with the defined class by means of the

RULES clause. The two rules are defined by using

the RULE template.

When there are alarms in the network, the

integrated expert system makes a study of the events

produced.

...

(31/01 1115.1836 Station1 7_TX_C2 Station4 ALARM) n

(31/01 1116.2142 Station1 7_TX_C2 Station4 ALARM) n+1

...

After an analysis, the management actions in the

expert rules are executed. The connection error

returns the following error messages, indicate

problems that require corrective action.

The first rule powerErrorCTR190, is in charge of

detecting failures in the power supply of the device;

the second rule linkCTR190, is devoted to the

detection of errors in the data transmission module.

FIRE 1: linkCTR190 f-2

Severity 4.

Diagnostic: Mistake in transmission Station4.

Recommendation: Revise transceiver.

1 rules fired.

Run time is 0.074 seconds, 27.0270 Rules/Sec.

6 PROTOTYPE VALIDATION

Validation is essential to the decision-making

success of NOMOS+ and to its continued use.

Validation constitutes an inherent part of the

knowledge based expert system development for

NOMOS+ and is intrinsically linked to the

development cycle (Giarratano, 2005).

To verify the system we feed it with an alarms

arbitrary amount. NOMOS+ has been validated with

respect to the following aspects: system validation

using test cases, validation by case studies,

validation against human experts, validation against

tough cases and validation on site, etc. The result of

this proof is included in Table 1.

APPLYING INTEGRATED EXPERT SYSTEM IN NETWORK MANAGEMENT

105

Table1: Prototype Testing Results.

Alarms

Initial Number

Number

After Filtration

Filtered

Alarms

Fired Rules

Proceeding

time

Rules/Sec.

Indications

to the Operator

100 1 99 51 0,118 Sec. 432,2034 1

200 10 95 102 0,412 Sec. 247,5728 6

300 31 89,6 155 1,250 Sec. 124,0000 20

400 31 92,25 201 1,438 Sec. 139,7775 16

500 32 93,6 254 2,975 Sec. 85,3782 19

600 38 93,66 293 5,249 Sec. 55,8202 16

700 44 93,71 346 17,982 Sec. 19,2415 18

800 55 93,125 394 26,938 Sec. 14,6262 23

From these result we can establish the following

conclusions:

- The expert system, with over 200 operation rules,

has produced excellent results which, after extensive

field-testing, proved to be capable of filtering 90%

of produced alarms with a precision of 95% in

locating them.

- As noted above, the NOMOS+ performs

satisfactorily with about a 95% rate of success in

real cases.

- The speed of the system improves diminishing the

number of alarms on which the rest of rules act.

It is noted that the performance of NOMOS+

depends considerably in the facts happened. In the

same way the more information is input, chances of

diagnosing the likely causes of the problems in the

network is increased.

7 CONCLUSIONS

Current networks are very complex and demand

ever-increasing levels of quality, making their

management a very important aspect to take into

account. Network management systems are based on

Client/Server architecture, and consist of a Manager

(offering user interface for the network

administrator), Agents (on managed network

devices), a protocol (in between the Manager and the

Agents) and a Management Information Base

(describing the properties of the managed device).

The traditional model of network administration has

certain deficiencies that we have tried to overcome

by using a model of intelligent integrated

management. To improve the techniques of expert

management in a communications network, we

propose the possibility of integrating and

normalizing the expert rules of management within

the actual definition of the managed objects.

Through the integration of the knowledge within the

new extension the GDMO+ standard, we can

simultaneously define the management information

and knowledge. Thus, the management platform is

more easily integrated and allows a better adaptation

for the network management.

To achieve this goal we build a prototype, an

expert system integrated is developed as a rule-based

expert system which is a computer program using

integrated IF-THEN rules.

We conclude pointing out an important aspect of

the obtained integration: by using only and

exclusively the extended GDMO specification, the

administration platform will be able to obtain the

management information necessary with respect to

the managed objects as well as the expert rules of

management that make up the knowledge base of the

expert system.

ACKNOWLEDGEMENTS

The work described in this paper has been supported

by the Spanish Ministry of Education and Science

(MEC: Ministerio de Educación y Ciencia) through

project reference number DPI2006-15467-C02-02.

REFERENCES

Morris, S. B., (2003). Network Management, MIBs and

MPLS: Principles, Design and Implementation.

Prentice Hall

Clemm, A., (2006). Network Management Fundamentals.

Cisco Press.

ISO/IEC. (1992). Structure of management information -

Part 4: Guidelines for the definition of managed

objects. CCITT X. 722 / ISO 10165-4. Geneva.

ITU-T. (1996). Principles for a Telecommunications

Management Network (TMN). Rec. M.3010.

Hebrawi, B. (1995). GDMO, Object modeling and

definition for network management. Technology

appraisals

Leon, C., Mejias, M., Luque, J., Gonzalo, F. (1999).

Expert System for the Integrated Management of a

Power Utility's Communication System. IEEE Trans

on Power Delivery, Vol. 14, No. 4, 1208-1212

Martín, A., León, C., Monedero, I. (2006). The Evolution

of OSI Network Management by Integrated the Expert

Knowledge. Publisher Springer Berlin / Heidelberg.

LNCS, 402-409.

Garcia, R.C.; Cannady, J. (2001). Boundary expansion of

expert systems: incorporating evolutionary

computation with intrusion detection solutions.

SoutheastCon. IEEE, 96-99.

Giarratano, J. C., Riley, G. D., (2005). Expert Systems:

Principles and Programming. Book, Brooks/Cole

Publishing Co.

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