Detection and mitigation of abnormal traffic behaviour in autonomic networked environments

Marnerides, A., Pezaros, D. and Hutchison, D. (2008) Detection and mitigation of abnormal traffic behaviour in autonomic networked environments. In: ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT), Madrid, Spain,

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Publisher's URL: http://doi.acm.org/10.1145/1544012.1544063

Abstract

Autonomic network environments are required to be resilient. Resilience is defined as the ability for a network to provide and maintain an acceptable level of service in the face of various challenges to normal operation [1]. Traffic abnormalities are a great challenge and it is vital for any network to be supported by resilient mechanisms in order to detect and mitigate such events. In this document we present our measurement-based resilience architecture and we argue that the correct combination of already proposed theoretical methodologies and mechanisms present in our architecture compose a powerful defence mechanism that satisfies autonomic properties such as self-protection and self-optimization. In addition we refer to our intentions of testing our proposed architecture within the ANA project [2] in order to justify our hypothesis.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Pezaros, Dr Dimitrios
Authors: Marnerides, A., Pezaros, D., and Hutchison, D.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
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