A Balanced Serial K-means Based Clustering Protocol for Wireless Sensor Networks

Wireless sensor networks consisting of nodes with limited battery power are deployed to collect useful information from a certain field. How to schedule the energy resource to improve energy dissipation is one of the challenges in implementation of such system. In this paper, we propose a balanced serial K-means based clustering protocol (BSK-means) for clustering the sensor nodes. The protocol based on K-means algorithm minimizes the amount of energy for the non-cluster head nodes to transmit their data to the cluster head, by minimizing the total sum of squared distances between all the non-cluster head nodes and the closest cluster centers. BSK-means balances each cluster to help in balancing the whole system load on each cluster head. Furthermore, the cluster-heads are selected in terms of two factors, the distance and residual energy. We present the algorithm of this new protocol, analyze its performance, and validate the algorithm by simulations. Both theoretical analyses and simulation results demonstrate that BSK-means can achieve better load-balance and prolong the system lifetime for the networks compared with LEACH

A Balanced Parallel Clustering Protocol for Wireless Sensor Networks Using K-means Techniques

For wireless sensor networks (WSNs), It Is a challenging task how to schedule the energy resource to extend the network lifetime due to the fact that WSNs are usually powered by limited and non-rechargeable battery. A clustering scheme is helpful In reducing the energy consumption by aggregating data at intermediate sensor nodes. In this paper, we propose a balanced parallel K-means based clustering protocol; we term it BPK-means protocol. In this new protocol, we use K-means algorithm to cluster the sensor nodes, the cluster-heads are then selected in terms of two factors, they are a) the distance from node to cluster-center, and b) the residual energy. BPK-means only requires local communications: each tentative cluster-head only communicates with their topologically neighboring nodes and other tentative cluster-heads when achieving a distributed clustering scheme. The algorithm thus has the attractive feature of parallel computations. Moreover, BPK-means further balances the clusters to improve intra-cluster communication consumptions. We present the algorithm of this new protocol, analyze its computing properties, and validate the algorithm by simulations. Both theoretical analyses and simulation results demonstrate that BPK-means can achieve better load-balance and less energy consumptions when compared with LEACH. In addition, the BPK-means protocol is able to distribute energy dissipation evenly among the sensor nodes, which then prolong the system lifetime for the networks significantly

PCA-Guided Routing Algorithm for Wireless Sensor Networks

An important performance concern for wireless sensor networks (WSNs) is the total energy dissipated by all the nodes in the network over the course of network lifetime. In this paper, we propose a routing algorithm termed as PCA-guided routing algorithm (PCA-RA) by exploring the principal component analysis (PCA) approach. Our algorithm remarkably reduces energy consumption and prolongs network lifetime by realizing the objective of minimizing the sum of distances between the nodes and the cluster centers in a WSN network. It is demonstrated that the PCA-RA can be efficiently implemented in WSNs by forming a nearly optimal K-means-like clustering structure. In addition, it can decrease the network load while maintaining the accuracy of the sensor measurements during data aggregating process. We validate the efficacy and efficiency of the proposed algorithm by simulations. Both theoretical analyses and simulation results demonstrate that this algorithm can perform significantly with less energy consumption and thus prolong the system lifetime for the networks