Energy‐efficient routing protocol and optimized passive clustering in WSN for SMART grid applications. (3rd November 2021) - Vinodha, Ramalingam; Durairaj, Sundarraj; Padmavathi, Sakkarai
Summary: Due to low cost, ease of implementation and flexibility of wireless sensor networks (WSNs), WSNs are considered to be an essential technology to support the smart grid (SG) application. The prime concern is to increase the lifetime in order to find the active sensor node and thereby to find once the sensor node (SN) dies in any region. For this reason, an energy‐efficient Dynamic Source Routing (DSR) protocol needs to provide the right stability region with a prolonged network lifetime. This work is an effort to extend the network's existence by finding and correcting the considerable energy leveraging behaviors of WSN. We build a comprehensive model based on real measures of SG path loss for different conditions by using the characteristics of WSN nodes and channel characteristics. This method also establishes a hierarchical network structure of balanced clusters and an energy‐harvesting SN. The cluster heads (CHs) are chosen by these SN using a low overhead passive clustering strategy. The cluster formation method is focused on the use of passive clustering of the particle swarm optimization (PSO). For the sake of eliminating delayed output in the WSN, energy competent dynamic source routing protocol (EC‐DSR) is used. Chicken swarm optimization (CSO) in which optimum cluster path calculation shall be done where distance and residual energy should be regarded as limitation. Finally, the results are carried out with regard to the packet distribution ratio, throughput, overhead management, and average end‐to‐end delay to demonstrate the efficiency of the proposed system. Abstract : Smart grid (SG) wireless sensor networks (WSN) are dependent sensor networks that implement a passive clustering strategy focused on particle swarm optimization to conduct cluster‐based routing to boost networking efficiency. The cluster forming in SG WSNs used energy modeling to effectively route packets via the chicken swarm optimization. The optimal architecture decisions for WSNs used in SG environments with a view to maximize the lifetime of the network are (i) installation of sensor nodes to avoid route errors, (ii) usage of maximum practicable packet size, and(iii) assignment of optimum transmission capacity for both data and the hardware. The findings obtained in this study indicate that it was easier to equate the proposed protocol with the other established methodologies for reduced energy usage and increased life span of the SG system.