ITR: Self-Stabilizing Networking Protocols for Distributed Systems

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Fault tolerant protocols are essential for providing various services (routing, group communication, broadcasting, multi-casting, etc.) in large, dynamic, distributed systems, where both processors and communication links can malfunction intermittently. For example, in mobile and ad hoc networks, the communication links are unreliable and some nodes may be unreachable for certain amounts of time. Such networks, consisting of mobile hosts that communicate via wireless radio channels, are being increasingly used for local area networks, law enforcement, military operations and a myriad of other applications. The traditional approach in designing fault tolerant protocols assumes an upper bound on the number of faults and involves a worst case design by fault masking. While this approachprovides 100% system availability under assumed conditions, the implementation becomes very expensive. At the same time there are numerous applications for which the lack of system availability for very short periods is acceptable. Self-stabilization is an ``optimistic'' model to design distributed fault tolerant systems; no upper bound on the number of faults is necessary, systems always reach a legitimate global state starting from any arbitrary (possibly illegitimate) state, and no central control is needed. However, system availability is not guaranteed during the convergence period.This research addresses the design and analysis of fault tolerant self-stabilizing protocols for global communication primitives for dynamic distributed systems, especially suitable for mobile ad hoc networks. The research focuses on several aspects:-- Create paradigms and guiding principles for designing self-stabilizing distributed algorithms;-- Explore methodologies for translating a conventional algorithm into a self-stabilizing analog;-- Discover and analyze self-stabilizing protocols for global communication primitives (resource center location, leader election, etc.) in a network;-- Explore fractional (rational) valued self-stabilizing algorithms as a way to obtain improved approximate solutions to otherwise NP-hard problems;-- Measure the degree to which self-stabilizing algorithms can contain a single fault.The research takes a combined theoretical and experimental approach, and applies its results to emerging distributed applications for ad hoc networks.