Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Abstract

The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.

Energy-Efficient Resource Allocation Strategy in Massive IoT for Industrial 6G Applications

“…In this system, the adjacent nodes communicates directly through a single-hop mode, and non-adjacent nodes use multiple hops for indirect communication. In this section, we use the idea of the DV-Hop algorithm to multiply the minimum number of hops and the average distance between two nodes to obtain the positional relationship between the unknown node and the anchor node [26], and then use the three sides. The measurement method solves the node position information, and finally predicts the position of the MA responsible for energy management in the cluster.…”

Recognition of Crop Diseases Based on Depthwise Separable Convolution in Edge Computing

“…A large number of nodes are randomly or systematically arranged in the monitoring area to sense and collect environmental data in real-time. For example, in the forest monitoring system GreenOrbs deployed in Wuxi, Jiangsu Province (China), wireless sensor nodes are placed on trees, and each node is embedded with temperature, humidity, light intensity, and carbon dioxide concentration sensors to monitor the forest environment and detect and prevent forest fire in real-time [ 13 ]. In the IoT system framework based on edge computing, wireless sensor nodes are mainly used to monitor the growth of crops and to communicate with edge computing nodes.…”

CWDV-Hop: A Hybrid Localization Algorithm With Distance-Weight DV-Hop and CSO for Wireless Sensor Networks

“…With the merits of faster convergence, fewer parameters and more robustness, Differential Evolution (DE) [31], [32] also can be used to solve the localization problem. In [31], the object function of the minimized optimization problem is established on the weighted squared errors of estimated distance and DE is applied to obtain the estimated location of unknown nodes instead of the multilateration method.…”

“…In [31], the object function of the minimized optimization problem is established on the weighted squared errors of estimated distance and DE is applied to obtain the estimated location of unknown nodes instead of the multilateration method. With the improvements of mutation operation and crossover operation of the basic DE algorithm, Han et al propose an improved DE algorithm which is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node [32]. Although the DE-based algorithms improve the positional precision of the unknown nodes, they also induce vast time overhead and energy consumption.…”