A New Parallelism-Capable Clustering Algorithm for Wireless Sensor Networks

In Wireless Sensor Networks (WSN), interactions of sensors to provide service to a specific task is a significant issue. Services provided by WSNs include collecting data from the environment and aggregating them to address queries, or processing the collected data and using the result to adjust environmental parameters such as temperature and moisture. In WSNs, a number of nodes may be simultaneously needed by some application, and these nodes usually need to interact with one another while running in parallel. It is desirable in WSNs that enough resources be assigned to the applications so that a typical application can acquire its needed resources as fast as possible. Distances among sensors assigned to an application typically constitute an important factor in saving communication energy. This paper concerns introducing a clustering algorithm to enhance the efficiency of resource assignment by reducing overall distances among cooperating sensors. In the proposed algorithm, clusters are formed with different sizes to assign just enough sensors to requesting application. Cluster sizes are determined based on an input file to the algorithm that contains the initial number of required clusters of each size. Several increasingly more inclusive versions of the proposed algorithm were studied that are reported in this paper. A performance analysis is provided that shows the proposed clustering algorithm outperforms the Means clustering algorithm from different perspectives.