Time Optimal Self-Stabilizing Spanning Tree Algorithms
نویسندگان
چکیده
This thesis presents time-optimal self-stabilizing algorithms for distributed spanning tree computation in asynchronous networks. We present both a randomized algorithm for anonymous networks as well as a deterministic version for ID-based networks. Our protocols are the rst to be time-optimal (i.e. stabilize in time O(diameter)) without any prior knowledge of the network size or diameter. Both results are achieved through a technique of symmetry breaking that may be of independent interest. Executions of randomized distributed algorithms contain a combination of nondeterministic and probabilistic choices; these choices often involve subtle interactions that often make such algorithms di cult to verify and analyze. Segala and Lynch have recently developed the Probabilistic Automata model to aid in reasoning about randomized distributed algorithms; their model is related to the earlier work of Lynch and Vaandrager. We use the Probabilistic Automata formalism to analyze the correctness and time complexity of our randomized algorithm for anonymous networks; in doing so, we demonstrate the e ectiveness of the formalism in reasoning about randomized algorithms. Thesis Supervisor: Dr. Shay Kutten Title: Manager-Distributed Computing, IBM T.J.Watson Research Center Thesis Supervisor: Nancy A. Lynch Title: Professor of Computer Science Thesis Supervisor: Roberto Segala Title: Research Associate, MIT Laboratory for Computer Science
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تاریخ انتشار 1993