Abstract
Energy efficiency represents a fundamental issue in WSNs, since the network lifetime period entirely depends on the energy of sensor nodes, which are usually battery-operated. In this article, an unequal clustering-based routing protocol has been suggested, where parameters of energy, distance, and density are involved in the cluster head election. Besides, the sizes of clusters are unequal according to distance, energy, and density. Furthermore, the cluster heads are not changed every round unless the residual energy reaches a specific threshold of energy. The outcomes of the conducted simulation confirmed that the performance of the suggested protocol achieves improvement in energy efficiency.
Highlights
Wireless sensor networks (WSNs) have been a significant field as a result of their increasing utilization in different applications
The results stated in table-2 and table-3, show the network lifetime represented in rounds corresponding to the percentage of dead nodes for the simulated protocols: the proposed, LEACH and Improved-LEAH respectively
It clearly shows that the improvement in the network lifetime for the proposed protocol over other simulated protocols
Summary
Wireless sensor networks (WSNs) have been a significant field as a result of their increasing utilization in different applications. The resources of sensor nodes are constrained for different reasons such as cost, size, energy, bandwidth, radio range. On top of these constraints, the energy which represents a big matter that requires to be wisely tackled when designing WSN systems. In the hierarchical-based routing such as clustering-based protocols, nodes can work either as a cluster member for sensing function or as a cluster head (CH) so as to forwarding data to the base station [4]. Clustering-based routing protocols have been more suitable to conserve energy in WSNs, especially in large-scale networks. In most clustering-based routing protocol algorithms, there are a specific number of phases such as setup, data transmission, and clustering topology maintenance.
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