Detection and Mitigation of Abnormal Traffic Behaviour in Autonomic Networked Environments

Marnerides, A. , Pezaros, D. P. 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, 09-12 Dec 2008, ISBN 9781605582108 (doi: 10.1145/1544012.1544063)

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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
Glasgow Author(s) Enlighten ID:Pezaros, Professor Dimitrios and Marnerides, Dr Angelos
Authors: Marnerides, A., Pezaros, D. P., 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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