Bug2 algorithm-based data fusion using mobile element for IoT-enabled wireless sensor networks

Abstract

In Wireless sensor networks, the hotspot problem is challenging because it degrades the data gathering process by isolating one or more sensor nodes. This challenge is mitigated by introducing mobile element-based data collection. This mobile element is scheduled in such a way that it traverses in the network to get data from the nodes and deposits it to the base station. The base station in the WSNs acts as a gateway for the Internet of things (IoT). However, identifying the efficient scheduling strategies in the WSNs is challenging and more challenging in the obstacle environment. To address these issues, we propose an Efficient Mobile Element Scheduling Protocol (EMESP) for data fusion using a popular robot path plan algorithm called the Bug algorithm. The EMESP works in three phases: i) identify the data fusion points, ii) choose the visiting order, and iii) pathfinding. We identify the data fusion points using the Balanced Iterative Reducing and Clustering hierarchies (BRICH) approach, followed by a lightweight geometric strategy for choosing the visiting order. Finally, the path between every two visiting points is constructed using the Bug algorithm. We implemented and tested the EMESP protocol using Python 3.10. x considering different metrics including lifespan, energy, throughput, statistical analysis, service time and traveling distances. The results of our proposed EMESP protocol shows superiority over the recently published existing works.

Keywords

• Wireless sensor networks
• Balanced iterative reducing and clustering hierarchies
• Bug algorithm
• Data fusion
• Machine learning
• Energy-efficiency