Title page for ETD etd-05102004-130036

Type of Document Master's Thesis
Author Thirunavukkarasu, Muthukumar
Author's Email Address mthiruna@vt.edu
URN etd-05102004-130036
Title Reinforcing Reachable Routes
Degree Master of Science
Department Computer Science
Advisory Committee
Advisor Name Title
Ramakrishnan, Naren Committee Co-Chair
Varadarajan, Srinidhi Committee Co-Chair
Ribbens, Calvin J. Committee Member
  • Multipath routing
  • Probabilistic algorithms
  • Reachability
  • Reinforcement learning
Date of Defense 2004-05-04
Availability unrestricted
Reachability routing is a newly emerging paradigm in networking, where the goal is to determine all paths between a sender and a receiver. It is becoming relevant with the changing dynamics of the Internet and the emergence of low-bandwidth wireless/ad hoc networks. This thesis presents the case for reinforcement learning (RL) as the framework of choice to realize reachability routing, within the confines of the current Internet backbone infrastructure. The setting of the reinforcement learning problem offers several advantages, including loop resolution, multi-path forwarding capability, cost-sensitive routing, and minimizing state overhead, while maintaining the incremental spirit of the current backbone routing algorithms. We present the design and implementation of a new reachability algorithm that uses a model-based approach to achieve cost-sensitive multi-path forwarding. Performance assessment of the algorithm in various troublesome topologies shows consistently superior performance over classical reinforcement learning algorithms. Evaluations of the algorithm based on different criteria on many types of randomly generated networks as well as realistic topologies are presented.
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