Abstract
Recently, localization accuracy of unknown nodes has become a critical and challenging issue for many Wireless Sensor Networks (WSNs) and Internet of Things (IoT) applications. Without associating the detected event with its precise geographic location will be surely considered meaningless for these applications. Among all localization algorithms, we observe that the DV-Hop localization algorithm is highly recommended to use in many fields of application due to its simplicity, feasibility, low cost, and no extra hardware requirements, but the localization error caused by the DV-Hop algorithm is relatively large. In this current work, based on both the DV-Hop algorithm and the Particle Swarm Optimization algorithm, we proposed four new localization algorithms to overcome the shortcomings of low accuracy that the basic DV-Hop based algorithms produce. The simulation results showed that the proposed localization algorithms can achieve a better localization performance in terms of accuracy in comparison with other existing algorithms such as basic DV-Hop, MDV-Hop and DV-Hop PSO under different random network topologies. We also observed that a significant localization accuracy is achieved by the proposed algorithm HWDV-HopPSO.
Highlights
T HE Internet of Things (IoT) concept and Micro-ElectroMechanical Systems [1], [2] allows designing and manufacturing a large amount of small wirelessly interconnected devices, which are able to detect, monitor, process and transmit physical phenomena such as temperature, pressure via Radio Frequency Identification (RFID), Zigbee, Internet, WiFi, Bluetooth, 3G, 5G, and so on
The effectiveness of our proposed algorithms is compared to the original DV-Hop, improved DVHop based on Particle Swarm Optimization (PSO) [38] and improved DV-Hop [43] and by thorough simulations
Additional phases have been added to the standard DV-Hop algorithm in order to minimize the localization error of unknown nodes in wireless sensor networks
Summary
T HE Internet of Things (IoT) concept and Micro-ElectroMechanical Systems [1], [2] allows designing and manufacturing a large amount of small wirelessly interconnected devices, which are able to detect, monitor, process and transmit physical phenomena such as temperature, pressure via Radio Frequency Identification (RFID), Zigbee, Internet, WiFi, Bluetooth, 3G, 5G, and so on. The authors in [35] introduced a new version of DVHop to improve the localization accuracy This improved algorithm applied the double communication radius method to modify the minimum hop count between sensor nodes. Based on this technique, the algorithm may be able to minimize the error of the estimated distance and the Sparrow Search Algorithm (SSA) is used instead of the least square technique. Many analysis performance scenarios have been carried out in order to confirm that the proposed particle swarm optimization based algorithm can significantly minimize the localization error compared to the basic DV-Hop. In [39], the authors introduced an improved version of the DVHop algorithm. The Bat algorithm is considered as an intelligent optimization strategy, which is applied to improve the computation of the average distance per hop of anchor nodes
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