Mr. Qingsong Ai Profile

Qingsong Ai

at Wuhan Univ of Technology

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Proceedings Article | 25 October 2005 Paper

A new energy-efficient hierarchical clustering algorithm for wireless sensor networks

Zude Zhou, Qingsong Ai

Proceedings Volume 6011, 60110B (2005) https://doi.org/10.1117/12.633945

KEYWORDS: Sensors, Sensor networks, Data communications, Data centers, Solar energy, Data processing, Networks, Environmental sensing, Digital electronics, Wireless communications

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Recent advances in wireless communications and microelectro-mechanical systems have motivated the development of extremely small, low-cost sensors that possess sensing, signal processing and wireless communication capabilities. A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the limited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads and then the clusterheads communicate the aggregated information to the processing center, may save energy. In this paper, we propose a distributed, randomized clustering algorithm to organize the sensors in a wireless sensor network into clusters. Our algorithm generates a hierarchy of clusterheads and observes that the energy savings increase with the number of levels in the hierarchy. Results in stochastic geometry are used to derive solutions for the values of parameters of our algorithm that minimize the total energy spent in the network when all sensors report data through the clusterheads to the processing center.

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