Mining clustering algorithm in wireless sensor networks
Shangping Dai, Pingping Wang, Li Gao, Shijue Zheng · 2008
One important critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is a scarce resource in a sensor node. Clustering technique has been proven to be an effective approach for data-gathering in wireless sensor networks. However, these data are characteristic of being heavily noisy, exhibiting temporal and spatial correlation. Data mining is a process in which a wide spectrum of data analysis methods is used. In order to extract useful information from such data, in this paper, we propose a novel cluster formation algorithm, which is called ACE-C algorithm according to mining sensor nodes. Compared to the ILP algorithm, the proposed algorithm increase the cluster head election mechanism, and the simulation results show that ACE-CILP algorithm achieves its intention of consuming less energy, equalizing the energy consumption of all the nodes, as well as extending the network lifetime perfectly.