An Efficient Distributed Deadlock Avoidance Algorithm for the AND Model
IEEE Transactions on Software Engineering
Non-Intrusive Detection of Synchronization Errors Using Execution Replay
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SRDS '99 Proceedings of the 18th IEEE Symposium on Reliable Distributed Systems
Efficient Generalized Deadlock Detection and Resolution in Distributed Systems
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Fast, Centralized Detection and Resolution of Distributed Deadlocks in the Generalized Model
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Stochastic analysis of distributed deadlock scheduling
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
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Efficient detection of a locally stable predicate in a distributed system
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Fast detection and resolution of generalized distributed deadlocks
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International Journal of Distributed Systems and Technologies
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We present a new algorithm for detecting generalized deadlocks in distributed systems. Our algorithm incrementally constructs and reduces a wait-for graph (WFG) at an initiator process. This WFG is then searched for deadlock. The proposed algorithm has two primary advantages: First, it avoids sending messages along the edges of the global wait-for graph (WFG), thereby achieving a worst-case message complexity of 2n, where n is the number of processes in the WFG. Since information must be obtained from every process reachable from the initiator, this is optimal to within a constant factor. All the existing algorithms for the same problem construct a distributed snapshot of the WFG. As this involves sending messages along the edges of the WFG, the best available message complexity among these algorithms is 4e-2n+2l, which is O(n/sup 2/) in the worst case, where e and l are the number of edges and leaves in the WFG, respectively. Second, since the information about a detected deadlock is readily available at the initiator process, rather than distributed among different processes, it significantly simplifies the task of deadlock resolution, and helps to reduce system overhead associated with the resolution. The time complexity of our algorithm is also better than or equal to the existing algorithms.