Upper and lower time bounds for parallel random access machines without simultaneous writes
SIAM Journal on Computing
A tree-based algorithm for distributed mutual exclusion
ACM Transactions on Computer Systems (TOCS)
Journal of the ACM (JACM)
An inherent bottleneck in distributed counting
Journal of Parallel and Distributed Computing - Parallel and distributed data structures
ACM Transactions on Programming Languages and Systems (TOPLAS)
Competitive concurrent distributed queuing
Proceedings of the twentieth annual ACM symposium on Principles of distributed computing
The Arrow Distributed Directory Protocol
DISC '98 Proceedings of the 12th International Symposium on Distributed Computing
DISC '01 Proceedings of the 15th International Conference on Distributed Computing
Brief announcement: concurrent counting is harder than queuing
Proceedings of the twenty-second annual symposium on Principles of distributed computing
Distributed queuing and applications
Distributed queuing and applications
Ordered Multicast and Distributed Swap
ACM SIGOPS Operating Systems Review
Dynamic analysis of the arrow distributed protocol
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
The cost of concurrent, low-contention Read&Modify&Write
Theoretical Computer Science - Foundations of software science and computation structures
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In both distributed counting and queuing, processors in a distributed system issue operations which are organized into a total order. In counting, each processor receives the rank of its operation in the total order, where as in queuing, a processor gets back the identity of its predecessor in the total order. Coordination applications such as totally ordered multicast can be solved using either distributed counting or queuing, and it would be very useful to definitively know which of counting or queuing is a harder problem. We conduct the first systematic study of the relative complexities of distributed counting and queuing in a concurrent setting. Our results show that concurrent counting is harder than concurrent queuing on a variety of processor interconnection topologies, including high diameter graphs such as the list and the mesh, and low diameter graphs such as the complete graph, perfect m-ary tree, and the hypercube. For all these topologies, we show that the concurrent delay complexity of a particular solution to queuing, the arrow protocol, is asymptotically smaller than a lower bound on the complexity of any solution to counting. As a consequence, we are able to definitively say that given a choice between applying counting or queuing to solve a distributed coordination problem, queuing is the better solution.