Distributed algorithms for finding centers and medians in networks
ACM Transactions on Programming Languages and Systems (TOPLAS)
Improved complexity bounds for center location problems on networks by using dynamic data structures
SIAM Journal on Discrete Mathematics
Self-stabilization
Clusterhead Controlled Token for Virtual Base Station On-Demand in MANETs
ICDCSW '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
The optimal location of replicas in a network using a READ-ONE-WRITE-ALL policy
Distributed Computing
Finding r-Dominating Sets and p-Centers of Trees in Parallel
IEEE Transactions on Parallel and Distributed Systems
Journal of Systems Architecture: the EUROMICRO Journal
A stabilizing algorithm for clustering of line networks
EURASIP Journal on Wireless Communications and Networking
| Hi-index | 14.98 |
In this paper, we present a self-stabilizing algorithm for finding clustering of tree networks on a distributed model of computation. Clustering is defined as the covering of the nodes of a network by subtrees such that the intersection of any two subtrees is at most a single node and the difference between the sizes of the largest and the smallest clusters is minimal. The proposed algorithm evenly partitions the network into nearly the same size clusters and places resources and services for each cluster at its clusterhead to minimize the cost of sharing resources and using the services. Due to being self-stabilizing, the algorithm can withstand transient faults and does not require initialization. The paper includes a correctness proof of the algorithm. It concludes with remarks on issues such as open and related problems and the application areas of the algorithm.