Localization in Wireless Sensor Networks Using DV-Hop Algorithm and Fruit Fly Meta-heuristic

Abstract

The sensor localization is one of many challenges in wireless sensor networks (WSNs). The perfect usage of WSNs largely depends on an efficient nodes' localization system. This paper proposed an improved localization algorithm in WSNs called DV-hop (FOA) that is based on the classical algorithm DV-Hop (Distance Vector-Hop) and the Fruit Fly metaheuristic to minimize the error on the nodes' position estimation. Fruit fly optimization (FOA) is preferment for the minimization problems due to its quick convergence and less of parameters. In this work, we initialize the flies in the initial search location defined by the DV-hop method and they are given the random value of direction and distance. Then, we find out the flies with the highest smell value using fitness and keep its positions, and we consider it the location of the target node. Simulation results in matlab show that the proposed algorithm DV-hop (FOA) has the better localization error than the original DV-Hop algorithm.

Optimizing the Average Hop-Count and Node Distance Using an Adjusted DV-Hop Algorithm with a Distance Error Rate

“…As a result, each unknown node {U?m} can calculate its distance to the nearest anchor {Ai} by applying Eq. (2).…”

“…Several application areas rely on localisation systems: -Wildlife monitoring, -Home automation, -Industrial control and, -Permanent monitoring. Many researchers have addressed this issue by proposing localisation heuristics [2,3], based as a whole, on special known nodes called "anchors" that are equipped with GPS that know their positions. The importance of a localisation system is that it allows us to sort out where the measurements were taken by the event capture system.…”

An Improved Algorithm Based on Chicken Swarm Optimization for Localization in Wireless Sensor Networks

“…But there are many negatives recorded by the early methods inspired from nature in terms of network resources used and the accuracy of localization and com all optimization methods exist the problem of local minimum has been raised, and to resolve them very recently many other techniques have been used, such as: Bees optimization algorithms the year 2011 [10], in 2014 Firefly and Cuckoo Search algorithms have been proposed [11,12]. Two algorithms based on the fruit fly Optimization algorithm (FOA) are proposed in 2019 and 2021 respectively for node localization in WSN [13,14].…”