Abstract
Owing to the fact that the selection of cluster heads has a significant effect on the lifetime of the network, many researches have proposed various cluster head election methodologies for cluster-based WSNs. Although recent studies have focused on adaptive approaches, in which different parameters are assembled under a function, the effect of these parameters on cluster head election is not investigated in detail. In this paper, initially, a small-scale dataset is constructed by evaluating the death of the first, the half and the last node in a cluster-based WSN using three popular cluster head parameters, including the remaining energy of the nodes, the intra-cluster communication cost and the number of neighbours. In consideration of the results, a dynamically changeable coefficient based adaptive cluster head election, DCoCH, is proposed. The coefficients of the cluster head election parameters show alteration within three different periods of the lifetime of the network. DCoCH is compared with two recent adaptive based cluster head election methodologies for various WSN parameters and the results show that DCoCH outperforms equivalent approaches for different values of the location of the base station, the size of the network, the number of the nodes, the initial batteries of the nodes and the distribution of the nodes.
Highlights
Since the energy efficiency is one of the main problems in Wireless Sensor Networks (WSNs) consisting of resource constrained sensor nodes, hierarchical routing protocols have been widely used in literature [1]
Due to the responsibilities of collecting data from member nodes, performing data aggregation functions and transmitting data to the base station, selecting the best candidates as cluster heads (CHs) is an important issue for energy efficiency in cluster-based WSNs
In order to analyse the performance of DCoCH, FND and last nodes (LND) is estimated by conducting extensive simulations with OMNeT++ and the results are compared with PEECR and CATD for various WSN parameters, including the number of the nodes, the initial batteries of the nodes, the distribution of the nodes, the size of the network and the location of the base station (Table 4)
Summary
Since the energy efficiency is one of the main problems in Wireless Sensor Networks (WSNs) consisting of resource constrained sensor nodes, hierarchical routing protocols have been widely used in literature [1]. Apart from the randomized methodology, two other approaches are used in literature called static and adaptive, for determining CHs. Super nodes, usually having higher batteries and more powerful processing capabilities than ordinary sensor nodes, are positioned in a predefined location for carrying out CH roles in static CH election process. Usually having higher batteries and more powerful processing capabilities than ordinary sensor nodes, are positioned in a predefined location for carrying out CH roles in static CH election process This strategy minimizes energy consumption of the network, it is not suitable for WSNs, which usually include resource constrained homogenous sensor devices.
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