Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 12, Pages 10170-10186Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3050473
Keywords
Internet of Things; Wireless sensor networks; Agriculture; Peer-to-peer computing; Heuristic algorithms; Approximation algorithms; Optimization; Approximation algorithm; restricted deployment locations; solar insecticidal lamps Internet of Things (SIL-IoTs); weighted set cover (WSC) problem; weighted SIL deployment problem (wSILDP); wireless sensor network (WSN)
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Funding
- Research Start-Up Fund for Talent Introduction of Nanjing Agricultural University [77H0603]
- National Natural Science Foundation of China [62072248, 61902188]
- Science and Technology Innovation Project of Xuzhou [KC18004]
- China Postdoctoral Science Foundation [2020T130304, 2019M651865]
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In this study, the weighted deployment problem of solar insecticidal lamps in agricultural Internet of Things is addressed, and a layered deployment method based on greedy algorithm is proposed to optimize the deployment locations through two phases and three design operations for achieving minimum deployment cost and maximum total weight. Simulation results show that the proposed method outperforms three peer algorithms in terms of deployment cost and total weight.
As an important physical control technology, solar insecticidal lamp (SIL) can effectively prevent and control the occurrence of pests. The combination of SILs and wireless sensor networks (WSNs) initiates a novel agricultural Internet of Things (IoT), i.e., SIL-IoTs, to simultaneously kill pests and transmit pest information. In this article, we study the weighted SIL deployment problem (wSILDP) in SIL-IoTs, where weighted locations on ridges are prespecified and some of them are selected to deploy SILs. Different from the existing studies whose optimization objective is to minimize the deployment cost, we consider the deployment cost and the total weight of selected locations jointly. We formulate the wSILDP as the weighted set cover (WSC) problem and propose a layered deployment method based on greedy algorithm (LDMGA) to solve the defined optimization problem. The LDMGA is composed of two phases. First, SILs are deployed layer by layer from the boundary to the center until the entire farmland is completely covered. Second, on the basis of three design operations, i.e., substitution, deletion and fusion, the suboptimal locations obtained in the first phase are fine-tuned to achieve the minimum deployment cost together with the maximum total weight for meeting the coverage and connectivity requirements. Simulation results clearly demonstrate that the proposed method outperforms three peer algorithms in terms of deployment cost and total weight.
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