An Energy-Efficient Layered Clustering Algorithm for Routing in Wireless Sensor Networks

An Energy-Efficient Layered Clustering Algorithm for Routing in Wireless Sensor Networks

Alphonse PJA (National Institute of Technology, Department of Computer Applications, Tiruchirappalli, India), Sivaraj C (National Institute of Technology, Department of Computer Applications, Tiruchirappalli, India) and Janakiraman T N. (National Institute of Technology, Department of Mathematics, Tiruchirappalli, India)
Copyright: © 2017 |Pages: 24
DOI: 10.4018/IJDST.2017070103
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Efficient energy management is a key issue in battery equipped wireless sensor networks (WSNs). The cluster based routing in WSNs is a prominent approach for energy conservation of the network which provides a hierarchical data collection mechanism. In order to maximize the energy conservation of sensor nodes, this paper proposes an Energy-efficient Layered Clustering Algorithm (ELCA) for routing in wireless sensor networks. ELCA constructs two layers of clusters to reduce the transmission rate and to balance the energy consumption of sensors. As early energy depletion of clusterheads (CHs) is a major limitation in clustering, this algorithm provides local remedy for energy suffering CHs through efficient CH substitution scheme. The performance of the proposed algorithm is analysed through extensive simulation experiments and verified by compared results with existing clustering algorithms.
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Wireless Sensor Networks (WSNs) consist of numerous tiny sensor nodes capable of performing wireless communication and one or more powerful sink(s). The ultimate functions of sensor nodes are data gathering and forwarding it to the sink. WSNs cover a wide range of applications like monitoring geographical areas, improving security, protecting natural resources, disaster prediction, intelligent transport management, health-care, smart home appliances and so on (Aziz et al., 2013). WSNs are mostly deployed in unapproachable hostile environments and lack specific infrastructure. Typically, sensors are heavily constrained by processing speed, storage, and communication bandwidth and especially power source, as it is battery operated (Wang et al., 2006). Among, energy constraint is an inevitable problem in the design of wireless sensor networks as it imposes a severe limitation on the lifetime of the network. Also, battery substitution is usually unachievable due to the massive number of nodes and inaccessible network deployment (Jariwala et al., 2014). As, nodes need to operate long duration with limited battery reserves (Abbasi et al., 2007), reducing their energy consumption through efficient energy conservation techniques will help prolong the network lifetime (Elmazi et al., 2015). Among sensors energy-consuming activities data transmission is prominent and it energy consumption rate is directly propositional to the communication distance between source and destination (Liu, 2015). Then, proficient routing of data packets in WSNs is a prominent approach to reduce a node's energy consumption.

In routing protocols, clustering a network is a better routing technique for efficient energy conservation and reducing data redundancy (Liu et al., 2010; Peng et al., 2015). Nodes, in clustering, are grouped into clusters and form each a distinguished node chooses as clusterhead (CH) (Dahnil et al., 2012). It is responsible for data gathering from cluster members, aggregate and forward it to the sink (Thakkar et al., 2014). Due to the many-to-one communication pattern, nodes, balanced energy consumption, load distribution and CH’s premature death are major drawbacks in the design of clustering in WSNs. Recent algorithms address these issues through periodic re-clustering or by reducing the coverage area of area of clusters, which are nearer to the sink. Others periodically re-locate the position of the sink (Keskin et al., 2011) or use multiple sinks. This proposed Energy-efficient Layered Clustering algorithm (ELCA) deals with the above-described problems by constructing a layered cluster structure for load distribution and reduces transmission rate by a two-level aggregation process. Further, it avoids CHs premature death by providing a local remedy for energy suffering CHs. Moreover, the performance of the proposed algorithm is compared to existing routing algorithms (Heinzelman et al., 2002; Hang et al., 2014; Xia et al., 2016).

The rest of the paper is organized as follows: Section 2 reviews the related works. Section 3 describes the preliminaries of the proposed algorithm. The network and radio model of the proposal are discussed in Section 4. Section 5 describes the problem statements and the proposed algorithm ELCA. Section 6 presents the simulation results and discusses its performance in contrast to simulations of other known protocols. Finally, Section 7 concludes the paper.

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