Distributed algorithms for finding centers and medians in networks
ACM Transactions on Programming Languages and Systems (TOPLAS)
PODC '86 Proceedings of the fifth annual ACM symposium on Principles of distributed computing
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
A Distributed Graph Algorithm: Knot Detection
ACM Transactions on Programming Languages and Systems (TOPLAS)
An O(nlog n) Unidirectional Algorithm for the Circular Extrema Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
A Distributed Algorithm for Minimum-Weight Spanning Trees
ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed computation on graphs: shortest path algorithms
Communications of the ACM
A Sophisticate's Introduction to Distributed Concurrency Control (Invited Paper)
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
A Single Source Shortest Path Algorithm for a Planar Distributed Network
STACS '85 Proceedings of the 2nd Symposium of Theoretical Aspects of Computer Science
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
Detecting termination of distributed computations using markers
PODC '83 Proceedings of the second annual ACM symposium on Principles of distributed computing
Maintaining the time in a distributed system
PODC '83 Proceedings of the second annual ACM symposium on Principles of distributed computing
IEEE Transactions on Parallel and Distributed Systems
On the Dynamic Initialization of Parallel Computers
The Journal of Supercomputing
Comments on "Distributed Algorithms for Network Recognition Problems"
IEEE Transactions on Computers
| Hi-index | 14.98 |
The problem of recognizing whether a given network is a tree, ring, star, complete graph, or bipartite graph is considered. Unified algorithms to recognize if the network is any one of the above are presented in each of three classes of algorithms-with centralized, decentralized, and noncentralized initiations. It is shown that the communication and time complexities of the centralized algorithm are linear in e and d, respectively, while those for decentralized algorithm are O(e+n log n) and O(n), respectively (e is the number of edges, n is the number of processors, and d is the diameter of the graph). The complexities for noncentralized algorithms are, respectively O(e+n log k), where k is the level number, and O(n).