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Open AccessArticle

Adaptive Measurement-Based Policy-Driven QoS Management with Fuzzy-Rule-based Resource Allocation

1
Centre for Secure Information Technologies, Queen’s University, Belfast, Northern Ireland, BT3 9DT, UK
2
School of Computing and Information Engineering, University of Ulster, Northern Ireland, BT52 1SA, UK
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Author to whom correspondence should be addressed.
Future Internet 2012, 4(3), 646-671; https://doi.org/10.3390/fi4030646
Received: 26 January 2012 / Revised: 5 June 2012 / Accepted: 27 June 2012 / Published: 4 July 2012
(This article belongs to the Special Issue Selected Papers from ITA 11)
Fixed and wireless networks are increasingly converging towards common connectivity with IP-based core networks. Providing effective end-to-end resource and QoS management in such complex heterogeneous converged network scenarios requires unified, adaptive and scalable solutions to integrate and co-ordinate diverse QoS mechanisms of different access technologies with IP-based QoS. Policy-Based Network Management (PBNM) is one approach that could be employed to address this challenge. Hence, a policy-based framework for end-to-end QoS management in converged networks, CNQF (Converged Networks QoS Management Framework) has been proposed within our project. In this paper, the CNQF architecture, a Java implementation of its prototype and experimental validation of key elements are discussed. We then present a fuzzy-based CNQF resource management approach and study the performance of our implementation with real traffic flows on an experimental testbed. The results demonstrate the efficacy of our resource-adaptive approach for practical PBNM systems. View Full-Text
Keywords: policy-based network management; fuzzy logic; resource allocation; admission control; resource management; converged networks policy-based network management; fuzzy logic; resource allocation; admission control; resource management; converged networks
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Yerima, S.Y.; Parr, G.P.; McClean, S.I.; Morrow, P.J. Adaptive Measurement-Based Policy-Driven QoS Management with Fuzzy-Rule-based Resource Allocation. Future Internet 2012, 4, 646-671.

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