A Fuzzy Non-dominance Approach for Network Routing with Inaccurate Information

Student thesis: Doctoral ThesisDoctor of Philosophy


Routing is one of the most essential functions in computer and telecommunications networks. As the network grows in size, complexity and mobility, it becomes more dicult to precisely determine the routing metrics due to networks' dynamic nature. As a result the information available for decision making of Quality of Service (QoS) routing is always inaccurate.
This thesis considers that network routing metrics are naturally uncertain due to the inaccurate information. A novel concept, fuzzy non-dominance multipath routing is developed for the network routing discovery and routing optimisation. The fuzzy non-dominance multipath routing de nes network routing problem in a fuzzy weight graph. The term fuzzy non-dominance routing used in this thesis is distinct from the conventional sense of fuzzy routing. Fuzzy non-dominance routing leads to the fuzzy Pareto-optimal multipath. A labelling setting algorithm is developed to nd out the limited as well as full non-dominated set of routes for network packets forwarding. This approach provides an alternative way to deal with the network routing and multipath routing optimisation problem with less computational and management costs.
This thesis proposed a framework for adopting fuzzy non-dominance routing into conventional structure networks. The simulation results covered fuzzy nondominance routing discovery by considering di erent network topologies, scales, fuzzy number designs and the grade of fuzziness. The thesis also addressed fuzzy non-dominance routing for general trac-engineering. Compare to conventional Open Shortest Part First routing, fuzzy non-dominance routing allows the network to cope with at most 60 % more demand. In addition, the thesis also studied the fuzzy non-dominance routing for optimising network routing convergence, quality of service routing and its applications in Mobile ad-hoc networks.
Date of Award2015
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorAbdol-Hamid Aghvami (Supervisor) & Vasilis Friderikos (Supervisor)

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