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Energy efficient data gathering using mobile sink in IoT for reliable irrigation.
- Source :
- Sustainable Computing: Informatics & Systems; Dec2023, Vol. 40, pN.PAG-N.PAG, 1p
- Publication Year :
- 2023
-
Abstract
- Due to the increasing world population, demand for food products have created the need to modernize and intensify agricultural operations through precision agriculture. The Internet of Things offers a wide variety of solutions for precision agriculture, but implementing it in the agriculture field imposes challenges to hardware and data communication in the network. Importantly, the sensor nodes have to be reliable for long periods with the limited available battery power. In this connection, the goal of this paper is to propose an efficient data collection algorithm which improves the network lifetime of the wireless sensor network (WSN), decreases the energy hole issue and reduces the data collection delay. In the proposed work, the rendezvous points (RPs) in the network are selected based on the energy level of the nodes, data packet density and the distance to the RPs. Then the mobile sink (MS) moves to the RPs in the shortest possible path to collect the data from the data-powered points. A hybrid meta-heuristic algorithm called WOAXGWO is proposed to find the shortest path for the MS. To assess the performance, the network's lifetime, energy consumption, and latency are considered. Simulation findings show the effectiveness of the proposed algorithm and are validated on a coconut farm to demonstrate its reliability. • WOAXGWO algorithm is proposed to alleviate premature convergence. • Proposed data collection algorithm first determines the optimal set of RPs. • Mobile sink determines the shortest path to visit all the RPs and reduces the delay. • The proposed work is implemented in real-time coconut farm to prove its reliability. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22105379
- Volume :
- 40
- Database :
- Supplemental Index
- Journal :
- Sustainable Computing: Informatics & Systems
- Publication Type :
- Academic Journal
- Accession number :
- 173854328
- Full Text :
- https://doi.org/10.1016/j.suscom.2023.100916