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Application of Agent-Oriented Techniques to Network Supervision. Babak Esfandiari, Mitel Corporation. Different opportunities for agents in networks. Routing Network Management Network Supervision GDMO/CMIS TMN. Network Supervision Problematic. Fault detection

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application of agent oriented techniques to network supervision

Application of Agent-Oriented Techniques to Network Supervision

Babak Esfandiari,

Mitel Corporation

different opportunities for agents in networks
Different opportunities for agents in networks
  • Routing
  • Network Management
    • Network Supervision
    • GDMO/CMIS
    • TMN
network supervision problematic
Network Supervision Problematic
  • Fault detection
  • Alarm filtering and qualification
  • Multiple and cascading faults
  • ...
existing attempts
Existing attempts
  • Mostly use of expert systems for diagnosis ([Gaiti] [Garijo]…)
    • Use of agent-oriented architectures (?)
    • Revealed the importance of explicit representation of Time
    • No high-level communication between network management platforms
    • Acquisition of expertise is still a bottleneck
chronicles
Chronicles

Chronicle RobotLoadMachine {

event (Robot: (outRoom, inRoom), e1);

event (Robot: (inRoom, outRoom), e4);

event (MachineInput: (unLoaded, loaded), e2);

event (Machine: (Stopped, Running), e1);

e1 < e2;

1’ <= e3 - e2 <= 6’;

3’ <= e4 - e2 <= 5’;

hold (Machine: Running, (e2, e2));

hold (SafetyConditions: True, (e1, e4));

when recognized {report “Successful load”;} }

some theoretical speculations agents and osi layers
Some theoretical speculations: Agents and OSI layers
  • Using Newell’s Knowledge Level as the highest communication layer?
    • Expressing applications behaviors in “rational” terms (Beliefs, Desires, Intentions, …)
    • Communicating such terms using high-level interaction languages (KIF/KQML?) and protocols
interface agents
Interface Agents

“A program that […] provides assistance to a user dealing with a particular application. Such agents learn by watching over the shoulder of the user and detecting patterns and regularities…” (Maes)

use of bdi to specify the agent s behavior
Use of BDI to specify the agent’s behavior
  • Trust as a modal operator
  • B(a,f) Λ Trusts(a,b,f) -> K(a,f)
  • Trusts(a,a,f) ?
  • Trusts(a,human operator,*)
  • Trusts(a,b,f) with b := other agent ?
learnability of chronicles a set of oracles
Learnability of chronicles:a set of Oracles
  • PASSIVE: supplies events and actions
  • PASSIVES: PASSIVE + no overlapping
  • ACTIVEMQ: {events}+action -> yes/no
  • ACTIVEEQ:chronicle ->yes/(no+example)
learnability of chronicles results
Learnability of chronicles:Results
  • With one chronicle per action:
    • positive with PASSIVES
    • positive with ACTIVEMQ+ PASSIVE
  • If more than one chronicle per action:
    • negative with any oracle
  • Difficulties:
    • overlapping
    • x chronicles/action
    • where find such oracles ?
the learning system
The Learning System

3 steps:

  • Chronicle creation
  • Chronicle evaluation
  • Chronicle confirmation
an example 1
An example (1)

Evaluation of: a b c -> a

Unconfirmed chronicle base:

1: a b c d -> a Trust: 1

2: a b c e -> a Trust: 1

3: a b c f -> b Trust: 2

Confirmed chronicle base:

1: a b c g -> g Trust: 3

an example 2
An example (2)

Unconfirmed chronicle base:

1: d -> a Trust: 1

2: e -> a Trust: 1

3: a b c f -> b Trust: 2

Confirmed chronicle base:

1: a b c g -> g Trust: 3

2: a b c -> a Trust: 3

magenta management application or multi agent assistant
MAGENTA: MAnaGEmeNT Application or Multi-AGENT Assistant ?
  • ObjectManager: processes the query
  • CommunicationManager: sends and receives messages
  • EventManager: triggers event notifications
  • Management Application: processes the events and publishes queries
experimentation
Experimentation
  • The local network
  • Transpac data
  • Robot behavior pattern detection
  • Help to a Smalltalk programmer
  • Overlapping management
  • Collaborative learning
finding other oracles collaborative assistance
Finding other oracles:Collaborative assistance
  • Presentation protocol
  • Matchmaking protocol
  • Query protocol
conclusion and perspectives
Conclusion and perspectives
  • Summary:
    • Use of Interface Agents in Network Supervision
      • Theoretical results on chronicle learning
      • Appropriate algorithms
    • Use of Network Management standards to build an Agent Development platform
  • Next:
    • Improve the algorithms (first order, partial order)
    • Big scale experimentation
    • Other applications of MAGENTA: remote programming, distributed debugging, ...
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