Value-oriented network management

Schwartz, Shalom H.; Zager, D.

doi:10.1109/noms.2000.830424

Cited by 7 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most fault localization techniques [7], [17], [19], [27], [28], [41], [54], including the technique introduced in this paper, rely on a fault propagation model, which represents information about the impact of system entity failures on other system entities. Fault propagation models expose information about the system structure that is useful to fault localization while hiding information that is irrelevant to this process.…”

Section: Belief Network As Fault Propagation Modelmentioning

confidence: 99%

“…Fault management systems model fault propagation by representing either causal relationships among events [7], [19], [54] or dependencies among (both abstract and physical) communication system entities [17], [27], [28], [41]. A dependency-graph representation is more natural as it encodes perceivable relationships among system components.…”

Section: Belief Network As Fault Propagation Modelmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic Fault Localization in Communication Systems Using Belief Networks

Steinder

Sethi

2004

IEEE/ACM Trans. Networking

152

100

View full text Add to dashboard Cite

Abstract-We apply Bayesian reasoning techniques to perform fault localization in complex communication systems while using dynamic, ambiguous, uncertain, or incorrect information about the system structure and state. We introduce adaptations of two Bayesian reasoning techniques for polytrees, iterative belief updating, and iterative most probable explanation. We show that these approximate schemes can be applied to belief networks of arbitrary shape and overcome the inherent exponential complexity associated with exact Bayesian reasoning. We show through simulation that our approximate schemes are almost optimally accurate, can identify multiple simultaneous faults in an event driven manner, and incorporate both positive and negative information into the reasoning process. We show that fault localization through iterative belief updating is resilient to noise in the observed symptoms and prove that Bayesian reasoning can now be used in practice to provide effective fault localization.Index Terms-Fault localization, probabilistic inference, root cause diagnosis.

show abstract

Section: Belief Network As Fault Propagation Modelmentioning

confidence: 99%

Section: Belief Network As Fault Propagation Modelmentioning

confidence: 99%

Probabilistic Fault Localization in Communication Systems Using Belief Networks

Steinder

Sethi

2004

IEEE/ACM Trans. Networking

152

100

View full text Add to dashboard Cite

show abstract

“…This layered correlation model is in compliance with recent work on modeling networks for supporting fault isolation and recovery [4,5].…”

Section: Introductionsupporting

confidence: 68%

“…We classify internal Yemanja events as either cause or symptom, similar to the classification in [5]. If an entity detects a failure of the corresponding device or layer,…”

Section: Entity Modelsmentioning

confidence: 99%

Yemanja-a layered event correlation engine for multi-domain server farms

Appleby

Goldszmidt²,

Steinder³

2001 IEEE/IFIP International Symposium on Integrated Network Management Proceedings. Integrated Network Management VII. Integra

View full text Add to dashboard Cite

Yemanja is a model-based event correlation engine for multi-layer fault diagnosis. It targets complex propagating fault scenarios, and can smoothly correlate low-level network events with high-level application performance alerts related to quality of service violations. Entity-models that represent devices or abstract components encapsulate entity behavior. Distantly associated entities are not explicitly aware of each other, and communicate through event propagation chains. Yemanja's statebased engine supports generic scenario definitions, prioritization of alternate solutions, integrated problem-state and device testing, and simultaneous analysis of overlapping problems.The system of correlation rules was developed based on device, layer, and dependency analysis, and reveals the layered structure of computer networks. The primary objectives of this research include the development of reusable, configuration independent, correlation scenarios; adaptability and the extensibility of the engine to match the constantly changing topology of a multi-domain server farm; and the development of a concise specification language that is relatively simple yet powerful.

show abstract

“…Calvet J.T and Girault C. jointly designed and developed the SDH synchronization network planning simulation platform, simulating the impact of different synchronization configurations [7]. Schwartz S. H. and Zager D. designed a discrete event-based telecommunications network simulation platform to simulate the failure process of various types of networks including SDH networks [8]. Ruepp S et al proposed a database-based SDH transmission network self-healing model simulation model, which focuses on the occurrence of simulated failures and business recovery processes [9].…”

Section: Introductionmentioning

confidence: 99%

Self-healing Model Construction and Simulation of Power SDH Transmission Network

Wang¹,

Yu²,

Ren³

et al. 2018

Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

View full text Add to dashboard Cite

With the rapid development of Synchronous Digital Hierarchy (SDH) technology, it has been more and more widely used in power communication networks. The power communication network has high requirements on the reliability of data transmission, and the self-healing ring has the advantages of automatic fault recovery, high reliability, flexible networking, and simple implementation, thus becoming an indispensable part of the construction of power communication SDH networks. How to effectively evaluate the self-healing ability of SDH and improve the performance of the transmitted services has become an urgent problem to be solved. In the actual operation of the network, the selfhealing capability of SDH cannot be accurately and effectively evaluated. Therefore, on the Exata simulation platform, the SDH transmission network equipment, network, services and other resources and self-healing behavior are modeled to achieve the SDH. Transmission network "fault occurrence-fault detection-fault recovery" this self-healing process simulation. Finally, a comparative evaluation of the availability of access networks and backbone networks was carried out for a protection network in a certain area, verifying that the channel protection function of SDH self-healing rings can effectively improve the security and reliability of the power grid.

show abstract

Value-oriented network management

Cited by 7 publications

References 5 publications

Probabilistic Fault Localization in Communication Systems Using Belief Networks

Probabilistic Fault Localization in Communication Systems Using Belief Networks

Yemanja-a layered event correlation engine for multi-domain server farms

Self-healing Model Construction and Simulation of Power SDH Transmission Network

Contact Info

Product

Resources

About