Neighbor-Node Analysis based Min-Max Algorithm to Generate Optimized Route in WSN

Abstract

WSN is a real-time adhoc network in which sensor devices and equipment are defined with energy and coverage limits. In such a network, one primary requirement is defining an effective routing approach to draw effective communication. The presented work improves the existing shortest path algorithm with some defined constraints. The result is about generating the most straightforward path under the condition of congestion. An energy-effective shortest path is defined in the existing work, but the proposed work has defined some more constraints while defining the communication route. This work suggests a network routing protocol based on energy, distance, load, and the node failure ratio. Each parameter will be assigned a specific priority, and respectively, the fuzzy rules are defined. Based on the fuzzy decision, the next intermediate node is elected. Finally, a congestion-free route is obtained over the network. The simulation results identified that the proposed protocol reduced the energy consumption, Hop count, and route switches against Shortest Path, Greedy, and other state-of-art Protocols. The proposed protocol improved the network life, reliability, and communication without compromising the cost. The proposed protocol improved the PDR ratio by 13.5% against the shortest path algorithm, 9.33% against the Greedy approach, and 3.23% against Srivastava et al. algorithm. A significant gain in network life is achieved by the proposed protocol as the number of dead nodes for the proposed protocols are only 13 whereas in case of the shortest path, greedy and Srivastava et al. algorithms the dead nodes were 23, 20, and 16. The proposed protocol improved the network stability by reducing the route switching to 7. The route switches in the shortest path, greedy and Srivastava et al. protocols are 19, 16, and 11. These results verified that the proposed protocol has achieved higher stability, improvement in network life, © 2022 ACM.