LEVY FLIGHT GOLDEN JACKAL OPTIMIZATION BASED CLUSTER HEAD SELECTION (LFGJO-CHS) AND DATA TRANSMISSION FOR EDGE COMPUTING WSN

Abstract

  Wireless Sensor Network (WSN) model, sensor nodes are extensively spread in the Internet of Things (IoT). It plays a major role in energy production and longevity. On the other hand, WSN nodes have restricted energy, making short-term data transmission a difficult task.  This research introduces a novel routing protocol to reduce node energy consumption and increase network lifetime by clustering protocol. Optimized Two-Layer Clustering Routing Protocol (OTLCRP) based on edge computing and Levy Flight Golden Jackal Optimization (LFGJO) is used to clustering. The edge server is able to observe the fundamental WSN nodes and help with selecting CH nodes. Clustering may design to improve the efficiency of CHS by using a LFGJO. CHS process is based on the energy, residual energy, average energy, node distance as major important factors for effectively improving routing efficiency. It satisfies the goal of minimizing network energy usage and extending network lifetime to some extent and it provides some practical usefulness. It stability the load and distance in the OTLCRP process. Results are measured using the metrics like number of data packets received, node remaining energy, network lifetime and Number of remaining nodes.