Principles of Mobile Communication
Principles of Mobile Communication
On Clustering Using Random Walks
FST TCS '01 Proceedings of the 21st Conference on Foundations of Software Technology and Theoretical Computer Science
Natural communities in large linked networks
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Stochastic local clustering for massive graphs
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A survey of clustering schemes for mobile ad hoc networks
IEEE Communications Surveys & Tutorials
Computational Intelligence in Wireless Sensor Networks: A Survey
IEEE Communications Surveys & Tutorials
Network coordination for spectrally efficient communications in cellular systems
IEEE Wireless Communications
Computer Science Review
Hi-index | 0.00 |
We consider distributed clustering of weighted graphs. Each node in the graph is represented by an agent, with agents independent of each other. The target is to maximize the sum weight of intra-cluster edges with cluster size constrained by an upper limit. To avoid getting stuck in not-too-good local optima, we approach this problem by allowing bad decision-making with a small probability that is dependent on the depth of local optima. We evaluate performance in a setting inspired by self-organizing coordination area formation for coordinated transmission in wireless networks. The results show that our distributed clustering algorithm cab perform better than a distributed greedy local search.