An adaptive coverage aware data gathering scheme using KD-tree and ACO for WSNs with mobile sink

• Published in: The Journal of supercomputing Vol. 78; no. 11; pp. 13530 - 13553
• Main Authors: Al Aghbari, Zaher, Khedr, Ahmed M., Khalifa, Banafsj, Raj, Pravija P. V.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2022; Springer Nature B.V
• Subjects: Adaptive algorithms; Ant colony optimization; Compilers; Computer Science; Energy consumption; Interpreters; Network topologies; Nodes; Processor Architectures; Programming Languages; Travel time; Wireless networks; Wireless sensor networks; Wireless sensor networks; Ant colony optimization; Mobile sink; Trajectory design; Travel route planning; KD-tree; Data gathering
• ISSN: 0920-8542; 1573-0484
• DOI: 10.1007/s11227-022-04407-5

While several Mobile Sink (MS)-based data gathering methods have been proposed for Wireless Sensor Networks, most of them are less adaptive to changes in network topology, and the planned MS trajectory cannot be refined to accommodate node failures. Hence, a KD-Tree-based scheme (KDT) is proposed, which is an adaptive and robust algorithm that reduces network energy consumption and data gathering delay. In contrast to many existing algorithms, the number of Rendezvous Points (RPs) are assigned dynamically by prioritizing the nodes’ coverage. Overlapping coverage of RPs is minimized, while guaranteeing 100% coverage of nodes. KDT is adaptive to network topology changes, and the planned MS trajectory can be refined to accommodate node failures. The shortest MS path is found using Ant Colony Optimization. Simulation results show that KDT requires approximately half the number of RPs and about 13% reduction in MS travel time compared to existing schemes.