Energy Efficient Cluster Formation Using A Multi-Criterion Optimization Technique for Wireless Sensor Networks
DOI: 10.1109/CCNC.2007.133 Conference: Consumer Communications and Networking Conference, 2007. CCNC 2007. 4th IEEE
In large scale wireless sensor networks clustering is often used for improving energy efficiency and achieving scalable performance. In this paper we present a novel energy efficient cluster formation algorithm based on a multi-criterion optimization technique. Our technique is capable of using multiple individual metrics in the cluster formation process as input while optimizing on the energy efficiency of the individual sensor nodes as well as the overall system. The proposed technique is implemented as distributed protocol in which each node makes its decision based on local information only. The feasibility of proposed technique is demonstrated with simulation results. The performance of the proposed method compares favorably with other well known clustering protocols with respect to energy consumed and network life time.
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- "The radio model adopted is, stated by Heinzelman et al . The following are the most widely used assumptions and model in sensor network simulation and analysis . Nodes are dispersed randomly following a uniform distribution in a 2-dimensional space and the location of the Base Station (BS) is known to all sensors. "
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- "Table 1 outlines the notation used in the following sections. We assume that cluster heads can be elected using any generic single-hop clustering protocol such as   . "
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ABSTRACT: Recent years have witnessed an increasing availability of heterogeneous sensor networks that consist of a large number of resource constrained nodes (sensors) and a small number of powerful resource rich nodes (actors). Such heterogeneous Wireless Sensor Actor Network (WSANs) offer improvement of sensor networks' capacity/coverage, energy conservation and network lifetime. This paper investigates the case where sensors are organized into clusters and mobile actors are used for maintaining an energy efficient topology by periodically manipulating their geographical position. We present an elegant technique that allows actor nodes to find an optimal geographical location with respect to their associated cluster heads such that the overall energy consumed is minimized. The proposed technique includes a weighted cost function based on the residual energy levels of cluster heads that allows the mobile actor to optimally fine-tune its geographical location. We present simulation results that demonstrate a significant increase of network lifetime over the traditional cluster based WSN deployments.
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