ACO-based mobile sink path determination for wireless sensor networks under non-uniform data constraints

• Published in: Applied soft computing Vol. 69; pp. 528 - 540
• Main Authors: D., Praveen Kumar, Amgoth, Tarachand, Annavarapu, Chandra Sekhara Rao
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2018
• Subjects: Ant colony optimization; Mobile sink; Network lifetime; Non-uniform data; Rendezvous points; Wireless sensor networks; Rendezvous points; Wireless sensor networks; Ant colony optimization; Network lifetime; Mobile sink; Non-uniform data
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2018.05.008

•An efficient mechanism to construct directed spanning tree to find forwarding node for each sensor node.•A new ACO-based algorithm for finding a near optimal set of RPs and tour length of the mobile sink.•A comprehensive validation of the proposed algorithm ACO-MSPD via simulation runs.•Simulation study of various parameter to know their impact on the network lifetime. In wireless sensor networks, a mobile sink is used to collect data from sensors by traversing the network periodically to prevent hotspot or energy-hole problem. In order to avoid the delay incurred by visiting all the sensor nodes, a mobile sink may allow visiting only a few number of locations or nodes referred as rendezvous points and remaining nodes send their data to the nearest rendezvous point. Finding an optimal set of rendezvous points will improve the data gathering process of the sink and also maximize the network lifetime. However, it is more challenging to find an optimal set of rendezvous points and traveling path of the mobile sink when the sensor node generates data unevenly. In this paper, we propose a new Ant Colony Optimization-based mobile sink path determination for wireless sensor networks. The objective of the proposed algorithm is to maximize the network lifetime and minimize the delay in collecting data from the sensor nodes. In the proposed algorithm, we devise an efficient mechanism to find a near-optimal set of rendezvous points and traveling path of the mobile sink to achieve the desired objectives. The proposed algorithm also adopts re-selection of rendezvous points to balance the energy consumption of the sensors. Through simulation runs, we show that the proposed algorithm outperforms the existing ones.