An energy‐efficient routing based on a hybrid improved whale artificial ecosystem optimization algorithm in WSN

Abstract Wireless sensor network (WSN) is an auto‐configured and baseless wireless network system to detect the physical scenarios or atmospheric situations like temperature, sound, pressure, pollutants, and so on. These investigations can be aided for the smooth transmission of data along with the networks. The current smart world exploits WSN in most applications, such as technical applications, industrial applications, low‐power embedded systems, and other smart communications. Even though it has so many applications, the available limited supply resource causes ill effects while transmitting large amounts of data. Hence, we can deem energy efficiency as a crucial factor that affects the performances of WSN. Processes such as routing, and for long‐lasting life span WSN requires more energy. Hence, to have an effective routine and enhanced life span of WSN, we propose a novel energy‐efficient routing protocol based on a hybrid improved whale artificial ecosystem optimization algorithm. To attain an energy‐efficient network it is ineluctable to choose an optimized cluster head and other nodes. These can be performed by evaluating various fitness functions of WSN. Henceforth, the nodes are organized and better routing can be obtained based on the fitness function values. This also improves the energy efficiency of the WSN and has been utilized to select the other forwarding nodes. Experimental analyses are conducted based on the deemed three scenarios which are based on the positioning of the base station (BS) and compared with other prior works. In all aspects, our proposed work has better performances than the other state‐of‐art works.