Optimized Hop Angle Relativity for DV-Hop Localization in Wireless Sensor Networks

Abstract

Smart multifunctional sensors integrated with wireless connectivity (also known as wireless sensor networks or WSNs) play an important role in the Internet of Things (IoT). Several challenges associated with WSNs have been researched and energy consumption represents the main limitation. Another major challenge is localization because a sensor or node should be self-contained and organized and have a low cost of integration. The range-free approach is promising due to its simplicity. Notably, it does not require additional logics and needs only key parameters, such as the number of hops and node locations. Distance-vector-hop-based localization (DV-Hop) is a pioneering range-free approach, and the corresponding localization approximation method does not require areas to be covered by nodes with known positions (also called known nodes or anchor nodes). However, the precision of this approach relies on several factors, including the node density and the method of determining the relation between the distance and the number of hops between two anchor nodes (i.e., hop size). Thus, this research enhances DV-Hop by: 1) reducing the approximation coverage to a specific area, thereby requiring fewer anchor nodes; 2) further decreasing the area using a bounding box; and 3) adopting particle swarm optimization (PSO) by integrating the number of hops and anchor nodes into the fitness function to improve the approximation precision. To evaluate the efficiency of the proposed scheme, the simulation results are compared with those of five recently proposed DV-Hop localization methods: iDV-Hop, DV-maxHop, Selective 3-Anchor DV-Hop, PSODV-Hop, and GA-PSODV-Hop.

Keywords

• Distance-vector-hop-based localization
• hop angle relativity
• localization
• particle swarm optimization
• wireless sensor networks