System designs for adaptive, distributed network monitoring and control

Li, H.; Yang, Shah-An; He, Xiaodong; Baras, John S.

doi:10.1109/inm.2001.918012

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…After a test node is chosen, the observation for this test may take advantage of the traditional SNMP paradigm by polling appropriate MIB variables; or, delegated (mobile) agents could be sent to the network elements to collect the data by using the management by delegation paradigm [7][9]. As one example of such an agent-based environment, the authors presented in [26] a couple of system designs for adaptive, distributed network monitoring and control, and in a sister paper also submitted to this conference [27], the authors discuss in more details the idea of change of logic. Further, the managed system could be divided into domains [33], and for each domain we could assign such an "intelligent" module that take charge of the fault and performance management for it [2][25].…”

Section: Discussionmentioning

confidence: 99%

A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks

Baras

2001

Management of Multimedia on the Internet

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In this paper, we present a framework for supporting intelligent fault and performance management for communication networks. Belief networks are taken as the basis for knowledge representation and inference under evidence. When using belief networks for diagnosis, we identify two questions: When can I say that I get the right diagnosis and stop? If right diagnosis has not been obtained yet, which test should I choose next? For the first question, we define the notion of right diagnosis via the introduction of intervention networks. For the second question, we formulate the decision making procedure using the framework of partially observable Markov decision processes. A heuristic dynamic strategy is proposed to solve this problem and the effectiveness is shown via simulation.

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Section: Discussionmentioning

confidence: 99%

A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks

Baras

2001

Management of Multimedia on the Internet

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“…Others have allowed device extensibility through call-back hooks and delegation of mobile agents [27] and Pluggable Service Device Models (PSDM) for abstraction of vendor/technology specifics [28]. Some systems also support evolutive Command Line Interfaces (CLIs) across a range of devices, such as the Lucent IP Network Configurator [29] and IP-CLIX [30].…”

Section: Evolutive Architecturesmentioning

confidence: 99%

A Policy-Driven Autonomous System for Evolutive and Adaptive Management of Complex Services and Networks

Sheridan-Smith

Leaney

O'Neill

et al.

12th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'05)

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Many existing management systems are not evolutive or adaptive, leading to multiplicity over time and increasing the management burden. Policy-based management approaches may assist in making networks less complex and more automated, but to date they have not yet been able to evolve to support new service sets or provide the capacity for differentiation.We present the architecture for a policy-based system named Pronto that helps to deal with these issues. Layered network and service models are built above an extensible virtual device model that supports heterogenous management interfaces. Interchangeable management components provide the basic building blocks to construct logical services. The integrated policy-driven service definition language automates the management of the services in a manner that is adaptive, dynamic and reactive to improve the user's overall service experience.

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System designs for adaptive, distributed network monitoring and control

Cited by 2 publications

References 11 publications

A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks

A Framework for Supporting Intelligent Fault and Performance Management for Communication Networks

A Policy-Driven Autonomous System for Evolutive and Adaptive Management of Complex Services and Networks

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