Providing an Efficient Model for Wireless Sensor Networks Using the Scenario of the Variable Sink Counts Based on the Particle Swarm Algorithm

1Javad Akbarirad, Mohammad
2Ghaemi, Reza
1Department of Computer Engineering, Science and Research Branch of Khorasan Razavi, Islamic Azad University, Neyshabur, Iran
2Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran
Sci. innov. 2019, 15(2):63-73
Section: The World of Innovations
Language: English
Introduction. A wireless sensor network is a set of independent sensor nodes, which are dispersed in a distributed manner to monitor and collect data in a geographic environment. One of these problems is the manner of node division in a set of multi-sink sensors.
Problem Statement. In fact, the main issue in this area is related to the division of sensor nodes between sinks so that reduced energy consumption and increased network life survival will be resulted. In this study, a solution has been provided to partition a multi-sink sensor network. Due to the nature of the problem of partitioning a multi-sink sensor network, the search space is very extensive and, on the other hand, proving that this issue is classified as NP-hard problems has made the presentation of a definitive solution very difficult.
Purpose. To develop a solution for distribution of sensor network with a few sinks.
Materials and Methods. Thus, given the broad search space of the problem ahead, particle swarm algorithm has been selected. In order to evaluate the proposed approach, MATLAB programming language has been applied.
Results. The proposed approach has been developed using the criteria of hop counts to the sink and also the number of cluster heads plus the power of particle search in particle swarm algorithm.
Conclusions. Study of these results in the form of two criteria of hop counts and the number of cluster heads using the scenario of the variable sink counts demonstrate that in the desired scenario, the proposed approach has been able to improve hop counts relative to the base method by 17% and the number of cluster heads by 59%.
Keywords: multi-sink, particle swarm algorithm, wireless sensor networks