A probabilistic clustering algorithm in wireless sensor networks
Hesong Huang, Jie Wu · 2006
Abstract — A wireless sensor network consists of nodes that can communicate with each other via wireless links. One way to support efficient communication between sensors is to organize the network into several groups, called clusters, with each cluster electing one node as the head of cluster. The paper describes a constant time clustering algorithm that can be applied on wireless sensor networks. This approach is an extension to the Younis and Fahmy method [1]. The simulation results show that the extension can generate a small number of cluster heads in relatively few rounds, especially in sparse networks.