Optimized Routing Enhancement for WSN with Balanced Load Mechanism

Mandeep Kaur, Balwinder Sohi
<span title="2019-04-30">2019</span> <i title="The Intelligent Networks and Systems Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hxhhpqr6nrfs5eblsflinrd2wa" style="color: black;">International Journal of Intelligent Engineering and Systems</a> </i> &nbsp;
Wireless Sensor Networks (WSNs) provides a great support and solution in the field of wireless technologies used in the industrial application. WSN faces serious reliability and load management issue when the power management terminology is enabled to prevent the network from excessive collision. This might result into a very low Packet Delivery Ratio (PDR), reduced network lifetime and high latency. In real time environment, a sensor node may suffer failure due to dust, corrosive agents and
more &raquo; ... hard weather etc. In that case, if the load increases on sensor node, it requires a reliable sensor node which can share the load. Reliable communication and load balancing among sensor nodes saves undesired consumption in collisions, data resending and data checking. This paper focuses on developing a novel framework enhancing the features of WSN to solve the reliability issue and load balancing problem with broadcast mechanism never used before in this scenario. The proposed framework utilizes a unique combination of Genetic Algorithm-Particle Swarm Optimization and Artificial Neural Network for load balancing architecture. The proposed architecture also utilizes some features of Ad hoc network also but with new terminology so that the packet reaches to the sink in timely fashion and maximum battery and network life along with minimized delay is attained. The proposed framework is evaluated using delay, energy consumption and throughput. One of the recent research works in this area is presented by Liu, Anfeng, et al and the proposed framework is also compared with the results of Liu, Anfeng, et al. By comparing the proposed results with existing, energy consumption of proposed work is reduced with better network lifetime by using the concept of load balancing technique.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22266/ijies2019.0430.23">doi:10.22266/ijies2019.0430.23</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eicpyaxky5c3vdl4oiihmyswhm">fatcat:eicpyaxky5c3vdl4oiihmyswhm</a> </span>
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