Abstract
In this paper, two clustering algorithms are proposed. In the first one, we investigate a clustering protocol for single hop wireless sensor networks that employs a competitive scheme for cluster head selection. The proposed algorithm is named EECS-M that is a modified version to the well known protocol EECS where some of the nodes become volunteers to be cluster heads with an equal probability. In the competition phase in contrast to EECS using a fixed competition range for any volunteer node, we assign a variable competition range to it that is related to its distance to base station. The volunteer nodes compete in their competition ranges and every one with more residual energy would become cluster head. In the second one, we develop a clustering protocol for single hop wireless sensor networks. In the proposed algorithm some of the nodes become volunteers to be cluster heads. We develop a time based competitive clustering algorithm that the advertising time is based on the volunteer node’s residual energy. We assign to every volunteer node a competition range that may be fixed or variable as a function of distance to BS. The volunteer nodes compete in their competition ranges and every one with more energy would become cluster head. In both proposed algorithms, our objective is to balance the energy consumption of the cluster heads all over the network. Simulation results show the more balanced energy consumption and longer lifetime.
Highlights
The sensor network is a collection of small-size, low-power, low-cost sensor nodes that have some computation, communication, storage and even movement capabilities
We propose two clustering algorithms which result in more balanced energy consumption and longer lifetime
We reviewed the energy balancing technique in wireless sensor networks via clustering
Summary
The sensor network is a collection of small-size, low-power, low-cost sensor nodes that have some computation, communication, storage and even movement capabilities These nodes can operate unattended, sensing the environment, generating data, processing data, and providing the data to users. A CH election algorithm must be distributed, energy-efficient, and load balanced [3] With this motivation, we propose a clustering algorithm as the second one in this paper that employs node’s residual energy for CHs’ selection and their distance to BS to form clusters. A variable competition range, which is derived from a recursive formula, is chosen which is proportional to the cluster’s size As it is shown later, these unequal clusters make the load to distribute evenly on the whole network and results in more nodes’ longevity.
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