WSN Routing Protocol Using a Multiobjective Greedy Approach

Seyed Reza Nabavi, Nafiseh Osati Eraghi, Javad Akbari Torkestani
<span title="">2021</span> <i title="Hindawi-Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6o4hgxplrbehxg4t53ub7zmfha" style="color: black;">Wireless Communications and Mobile Computing</a> </i> &nbsp;
Due to the widespread use of communication networks and the ease of transmitting and gathering information through these networks, wireless sensor networks (WSN) have become increasingly popular. Usability in any environment without the need for environmental monitoring and engineering of these networks has led to their increasing usage in various fields. Routing information from the sensor node to sink, so that node energy is consumed uniformly and network life is not reduced, is one of the
more &raquo; ... t important challenges in wireless sensor networks. Most wireless networks have no infrastructure, and embedded sensor nodes have limited power. Thus, the early termination of the wireless node's energy based on the transmission of messages over the network can disrupt the entire network process. In this paper, the object is designed to find the optimal path in WSN based on the multiobjective greedy approach to the near optimal path. The proposed model is presented in this method to transfer sensed data of the sensor network to the base station for the desired applications. In this method, the sensor nodes are identified as adjacent nodes based on their distance. The energy of all nodes initially is approximately equal, which decreases with the transfer of information between the nodes. In this way, when a node senses a message, it checks several factors for transmitting information to its adjacent nodes and selects the node with the largest amount of factors as the next hop. The simulation results show that the energy consumption in the network grids is almost symmetrically presented, and the network lifetime is reduced with a gentle slope that provides optimum energy consumption in the networks. Also, the packet transmission delay in the network reaches 450 milliseconds for the transmission of information between 15 nodes and 650 connections. Besides, network throughput increases by approximately 97%. It also shows better performance compared to other previous methods in terms of evaluation criteria.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6664669">doi:10.1155/2021/6664669</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/4b685bcab84e4adb810f2c93876c41ca">doaj:4b685bcab84e4adb810f2c93876c41ca</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qprlgvlpjfdg5f6ewvujknsflu">fatcat:qprlgvlpjfdg5f6ewvujknsflu</a> </span>
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