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)

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, 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
• ISBN: 9781605582108

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