Using data confluences in a distributed network with social monitoring to identify fault conditions

J.M. Aitken; T. Clarke

doi:10.1109/ETFA.2006.355347

Using data confluences in a distributed network with social monitoring to identify fault conditions

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper discusses the potential benefits of socially attentive monitoring in multi-agent systems. A multi-agent system with this feature is shown to detect and identify when an individual within the network fails to operate correctly. The system that has been developed is capable of detecting a range of common faults such as stuck at zero by allowing communication between peers within a software agent network. Further adaption to the model allows an improvement in system response without introduction of specific control design algorithms

Original language	Undefined/Unknown
Pages	8
DOIs	https://doi.org/10.1109/ETFA.2006.355347
Publication status	Published - 22 Sept 2006
Event	11th International International Conference on Emerging Technologies and Factory Automation - Prague, Czech Republic Duration: 20 Sept 2006 → 22 Sept 2006

Conference

Conference	11th International International Conference on Emerging Technologies and Factory Automation
Country/Territory	Czech Republic
City	Prague
Period	20/09/06 → 22/09/06

Access to Document

10.1109/ETFA.2006.355347

Cite this

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abstract = "This paper discusses the potential benefits of socially attentive monitoring in multi-agent systems. A multi-agent system with this feature is shown to detect and identify when an individual within the network fails to operate correctly. The system that has been developed is capable of detecting a range of common faults such as stuck at zero by allowing communication between peers within a software agent network. Further adaption to the model allows an improvement in system response without introduction of specific control design algorithms",

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AB - This paper discusses the potential benefits of socially attentive monitoring in multi-agent systems. A multi-agent system with this feature is shown to detect and identify when an individual within the network fails to operate correctly. The system that has been developed is capable of detecting a range of common faults such as stuck at zero by allowing communication between peers within a software agent network. Further adaption to the model allows an improvement in system response without introduction of specific control design algorithms

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