A novel approach of localization with Single Mobile Anchor using Salp Swarm Algorithm in Wireless Sensor Networks

Author(s):  
Shalli Rani ◽  
Pardeep Kaur ◽  
vinayakumar ravi ◽  
Gautam Srivast ◽  
Abu-Mahfouz A. M.

Abstract Wireless sensor networks (WSNs) have fabulous attributes to collect data by sensing the surrounding environment. WSNs have a large number of applications that are facing challenges of routing, security, deployment, prolonged lifetime, data computation, and localization. To achieve the high-level performance of WSNs, many researchers have proposed various computational Intelligence (CI) based algorithms for the above-mentioned challenges. The procedure to determine the location of the target node is called node localization. It is easy to determine the coordinates of static nodes accurately but challenging task for the mobile nodes. Localization accuracy directly affects the WSN’s performance. In this paper, a range-based and distributed method are proposed by using the application of the Salp Swarm Algorithm (SSA), and the simulation results are compared with existing approaches such as Particle swarm Optimization (PSO) and H-best Particle Swarm Optimization (HPSO). In this paper, a single mobile anchor node as a reference node traversing the entire network in the Hilbert path and localize the mobile target nodes that are randomly deployed in the networking area. The primary goal behind selecting the Hilbert trajectory is to reduce the issue of LoS. The simulation results show that the proposed method has low localization error and an approximate double number of localized nodes with less computing time as compared to existing methods.

2013 ◽  
Vol 427-429 ◽  
pp. 2540-2544 ◽  
Author(s):  
Jia Liang Lv ◽  
Ying Long Wang ◽  
Huan Qing Cui ◽  
Nuo Wei

Localization is one of the key technologies of wireless sensor networks, and the problem of localization is always formulated as an optimization problem. Particle swarm optimization (PSO) is easy to implement and requires moderate computing resources, which is feasible for localization of sensor networks. To improve the efficiency and precision of PSO-based localization methods, this paper proposes a novel three-dimensional PSO method based on weight selection (WSPSO). Simulation results show that the proposed method outperforms standard PSO and existing localization algorithms.


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