Abstract
In order to meet the requirements of emerging services, the future Internet will need to be flexible, reactive and adaptive. Network management functionality is essential in providing dynamic reactiveness and adaptability but current network management approaches have limitations and are inadequate to meet the relevant demands. In search for a paradigm shift, recent research efforts have been focusing on self-management principles. The PhD work presented in this paper proposes to investigate how autonomic principles can be extended and applied to fixed networks for quality of service (QoS) and performance management. The paper describes the two main research issues that will be addressed, namely (a) coordinated decision making in distributed environments, and (b) lightweight learning capabilities, and highlights their importance on realistic application scenarios for the emerging Internet.
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Awduche, D., Chiu, A., Elwalid, A., Widjaja, I., Xiao, X.: Overview and Principles of Internet Traffic Engineering. IETF RFC 3272 (May 2002)
Atlas, A., Zinin, A.: Basic Specification for IP Fast Re-route: Loop-free-Alternates. IETF RFC 5286 (September 2008)
Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing. IEEE Computer 36(1), 41–50 (2003)
Lavinal, E., Desprats, T., Raynaud, Y.: A generic multi-agent conceptual framework towards self-management. In: IEEE/IFIP Network Operations and Management Symposium, pp. 394–403 (April 2006)
Jiang, T., Baras, J.S.: Coalition Formation Through Learning in Autonomic Networks. In: Proceedings of the International Conference on Game Theory for Networks (GameNets 2009), Istanbul, Turkey, May 13-15, pp. 10–16 (2009)
Tcholtchev, N., Chaparadza, R., Prakash, A.: Addressing Stability of Control-Loops in the Context of the GANA Architecture: Synchronization of Actions and Policies. In: Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems. LNCS, vol. 5918, pp. 262–268. Springer, Heidelberg (2009)
Charalambides, M., Pavlou, G., Flegkas, P., Loyola, J., Bandara, A., Lupu, E., Russo, A., Dulay, N., Sloman, M.: Policy Conflict Analysis for DiffServ Quality of Service Management. IEEE Transactions on Network and Service Management (TNSM)Â 6(1) (March 2009)
Dietterich, T.G., Langley, P.: Self-Managing Networks. In: Mahmoud, Q.H. (ed.) Cognitive Networks: Machine Learning for Cognitive Networks: Technology Assessment and Research Challenges, ch. 5, pp. 97–120 (2007)
Tesauro, G.: Reinforcement Learning in Autonomic Computing – A Manifesto and Case Studies. IEEE Internet Computing 11(1), 22–30 (2007)
Gelenbe, E.: Steps towards self-aware networks. Communications of the ACM 52(7), 66–75 (2009)
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Tuncer, D., Charalambides, M., Pavlou, G. (2010). Towards Dynamic and Adaptive Resource Management for Emerging Networks. In: Stiller, B., De Turck, F. (eds) Mechanisms for Autonomous Management of Networks and Services. AIMS 2010. Lecture Notes in Computer Science, vol 6155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13986-4_12
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DOI: https://doi.org/10.1007/978-3-642-13986-4_12
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