4.8 Article

Optimal Deployment of Solar Insecticidal Lamps Over Constrained Locations in Mixed-Crop Farmlands

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 16, Pages 13095-13114

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3064043

Keywords

Approximation algorithms; Wireless sensor networks; Internet of Things; Peer-to-peer computing; Wireless communication; Monitoring; Heuristic algorithms; Approximation algorithm; connected set cover (CSC) problem; constrained SIL deployment problem (cSILDP); mixed-crop farmland; path-loss model; Solar insecticidal lamp-Internet of Things (SIL-IoTs); wireless sensor network (WSN)

Funding

  1. Research Start-Up Fund for Talent Introduction of Nanjing Agricultural University [77H0603]
  2. National Natural Science Foundation of China [62072248]
  3. Science and Technology Innovation Project of Xuzhou in 2018 [KC18004]

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This article focuses on the constrained SIL deployment problem in a mixed-crop farmland and proposes a hole-aware node deployment method based on the greedy algorithm, which achieves better performance than peer algorithms.
Solar insecticidal lamps (SILs) play a vital role in green prevention and control of pests. By embedding SILs in wireless sensor networks (WSNs), we establish a novel agricultural Internet of Things (IoT), referred to as the SIL-IoTs. In practice, the deployment of SIL nodes is determined by the geographical characteristics of an actual farmland, the constraints on the locations of SIL nodes, and the radio-wave propagation in a complex agricultural environment. In this article, we mainly focus on the constrained SIL deployment problem (cSILDP) in a mixed-crop farmland, where the locations used to deploy SIL nodes are a limited set of candidates located on the ridges. We formulate the cSILDP in this Scenario as a connected set cover (CSC) problem and propose a hole-aware node deployment method (HANDM) based on the greedy algorithm to solve the constrained optimization problem. The HANDM is a two-phase method. In the first phase, a novel deployment strategy is utilized to guarantee only a single coverage hole in each iteration, based on which a set of suboptimal locations is found for the deployment of SIL nodes. In the second phase, according to the operations of deletion and fusion, the optimal locations are obtained to meet the requirements on complete coverage and connectivity. Experimental results show that our proposed method achieves better performance than the peer algorithms, specifically in terms of deployment cost.

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