Energy‐efficient model using optimal route discovery based on adaptive spider monkey optimization model

Abstract

Summary During the past few years, wireless sensor networks (WSNs) have created a substantial interest because of their capabilities namely, self‐healing and self‐organizing under restricted network resources. Numerous WSN‐based routing algorithms are implemented to perform well, but the energy consumption of every data packet and information loss is more. Due to the power restriction in the sensor nodes, energy consumption is regarded as the major issue in networks that need to be minimized to improve the network lifetime. Hence, to conquer these consequences, this paper aims to propose an adaptive spider monkey optimization (ASMO)‐based effective optimal routing path from various sensor nodes with enhanced network lifetime. Here an ASMO is employed in selecting an optimal routing path. In addition to this, the proposed ASMO algorithm is capable of selecting energy‐aware routes by energy consumption. It also chooses the routes with minimum end‐to‐end delay using the bare least hop count criteria, thus enhancing the network life span. The results of the proposed method are compared with other methods such as DMEERP, EGSMRP, EEIABC, and RACO. The results reveal that the proposed approach consumed less amount of energy; hence, network lifetime is more when compared with other approaches.

Energy Effective Heterogeneous Grouping Ideal Transmission System With Fuzzy Identification in Uwsntion in Uwsn

“…Effects of other techniques like DMEERP, EGSMRP, EEIABC, and RACO are contrasted with those of the proposed method. The findings show that, in comparison to other approaches, the proposed strategy spent less energy, increasing network lifetime [24].…”

Double Q‐learning‐based adaptive trajectory selection for energy‐efficient data collection in wireless sensor networks

“…Wireless sensor network (WSN) plays a crucial role in modern society for a wide variety of applications, such as smart city, smart agriculture, military services, smart health care systems and so on 1 . It is an integral component of the Internet of Things (IoT) that monitors, regulates and transmits environmental‐related data to a central location 2 .…”