A distributed scheme for detecting communication deadlocks
IEEE Transactions on Software Engineering
Deadlock detection in distributed databases
ACM Computing Surveys (CSUR)
On characterization and correctness of distributed deadlock detection
Journal of Parallel and Distributed Computing
Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Deadlock models and a general algorithm for distributed deadlock detection
Journal of Parallel and Distributed Computing
Some Deadlock Properties of Computer Systems
ACM Computing Surveys (CSUR)
Distributed deadlock detection
ACM Transactions on Computer Systems (TOCS)
Efficient Detection and Resolution of Generalized Distributed Deadlocks
IEEE Transactions on Software Engineering
Weighted voting for replicated data
SOSP '79 Proceedings of the seventh ACM symposium on Operating systems principles
A distributed algorithm for detecting resource deadlocks in distributed systems
PODC '82 Proceedings of the first ACM SIGACT-SIGOPS symposium on Principles of distributed computing
A distributed algorithm for deadlock detection and resolution
PODC '84 Proceedings of the third annual ACM symposium on Principles of distributed computing
Deadlocks in Distributed Systems: Request Models and Definitions
FTDCS '95 Proceedings of the 5th IEEE Workshop on Future Trends of Distributed Computing Systems
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Deadlock detection in distributed asynchronous systems - such as distributed database systems, computer networks, massively parallel systems etc. - is peculiarly subtle and complex. This is because asynchronous systems are characterized by the lack of global memory and a common physical clock, as well as by the absence of known bounds on relative processor speeds and transmission delays. These difficulties imply also problems with performance analysis of distributed algorithms for deadlock detection. This paper deals with worst-case one-time complexity analysis of two well known distributed algorithms for generalized deadlock detection. The time complexity is expressed as a function of the diameter d and the longest path l of the wait-for-graph (WFG) characterizing a state of distributed system. First, the algorithm proposed by Bracha and Toueg is considered. It is shown that its time complexity is of 2d+2l. Then, we prove that the time complexity of Kshemkalyani and Singhal algorithm is of (d+ 1)+l.