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Machine learning for coverage optimization in wireless sensor networks: a comprehensive review

ANNALS OF OPERATIONS RESEARCH 2023年 1-67页

作者： Egwuche, Ojonukpe S. Singh, Abhilash Ezugwu, Absalom E. Greeff, Japie Olusanya, Micheal O. Abualigah, Laith Fed Polytech Dept Comp Sci Ile Oluji Ondo Nigeria Indian Inst Sci Educ & Res Bhopal India North West Univ Unit Data Sci & Comp 11 Hoffman St ZA-2520 Potchefstroom South Africa North West Univ Fac Nat & Agr Sci Sch Comp Sci & Informat Syst Vanderbijlpark South Africa Natl Inst Theoret & Computat Sci NITheCS Vanderbijlpark South Africa Sol Plaatje Univ Dept Comp Sci & Informat Technol ZA-8300 Kimberley South Africa Al Al Bayt Univ Comp Sci Dept Mafraq 25113 Jordan Lebanese Amer Univ Dept Elect & Comp Engn Byblos 135053 Lebanon Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman 19328 Jordan Middle East Univ MEU Res Unit Amman 11831 Jordan Yuan Ze Univ Coll Engn Taoyuan Taiwan Univ Sains Malaysia Sch Comp Sci George Town 11800 Malaysia Sunway Univ Malaysia Sch Engn & Technol Petaling Jaya 27500 Malaysia Appl Sci Private Univ Appl Sci Res Ctr Amman 11931 Jordan

In the context of wireless sensor networks (WSNs), the utilization of artificial intelligence (AI)-based solutions and systems is on the ascent. These technologies offer significant potential for optimizing services in today's interconnected world. AI and nature-inspired algorithms have emerged as promising approaches to tackle various challenges in WSNs, including enhancing network lifespan, data aggregation, connectivity, and achieving optimal coverage of the targeted area. coverage optimization poses a significant problem in WSNs, and numerous algorithms have been proposed to address this issue. However, as the number of sensor nodes within the sensor range increases, these algorithms often encounter difficulties in escaping local optima. Hence, exploring alternative global metaheuristic and bio-inspired algorithms that can be adapted and combined to overcome local optima and achieve global optimization in resolving wireless sensor network coverage problems is crucial. This paper provides a comprehensive review of the current state-of-the-art literature on wireless sensor networks, coverage optimization, and the application of machine learning and nature-inspired algorithms to address coverage problems in WSNs. Additionally, we present unresolved research questions and propose new avenues for future investigations. By conducting bibliometric analysis, we have identified that binary and probabilistic sensing model are widely employed, target and k-barrier coverage are the most extensively studied coverage scenarios in WSNs, and genetic algorithm and particle swarm optimization are the most commonly used nature-inspired algorithms for coverage problem analysis. This review aims to assist researchers in exploring coverage problems by harnessing the potential of nature-inspired and machine-learning algorithms. It provides valuable insights into the existing literature, identifies research gaps, and offers guidance for future studies in this field.

关键词： Wireless sensor networks coverage optimization Machine learning Deep learning Nature-inspired algorithms

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The Particle Swarm Differential Evolution Algorithm for Ecological Sensor Network coverage optimization

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JOURNAL OF INTELLIGENT SYSTEMS 2016年第3期25卷 335-350页

作者： Xu, Xing Hu, Na Ying, Weiqin Wu, Yu Zhou, Yang Jingdezhen Ceram Inst Coll Informat & Engn Jingdezhen 333403 Jiangxi Peoples R China Wuhan Univ State Key Lab Software Engn Wuhan 430072 Peoples R China South China Univ Technol Sch Software Guangzhou 510006 Guangdong Peoples R China Guangzhou Univ Sch Comp Sci & Educ Software Guangzhou 510006 Guangdong Peoples R China

The problem of coverage optimization is the challengingly important and key part in the research and application of ecology sensor network related with the ecological monitoring of Poyang Lake. A modified differential evolution algorithm (PSI-DE) combined with particle swarm intelligence is proposed to solve the coverage optimization problem. First, an improved version of the mutation rule combined with self-cognitive and social-cognitive items is introduced. Then, the influence on the coverage optimization performance of the PSI-DE algorithm brought by the five factors - namely, population size, number of iterations, sensing radius size, raster size, and number of nodes - is discussed and analyzed. The statistical results about the best coverage rate, average coverage rate, worst coverage rate, and variance are respectively obtained through a lot of simulation experiments. A series of the coverage rate curves, the line chart, and the node layout are drawn in this paper, and finally, the figures and the statistical results are proven to confirm each other.

关键词： coverage optimization differential evolution ecological sensor network hybrid algorithm particle swarm optimization

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coverage optimization algorithm based on control nodes position in wireless sensor networks

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第5期35卷 e4599-e4599页

作者： Li, Qiangyi Liu, Ningzhong Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Peoples R China MIIT Key Lab Pattern Anal & Machine Intelligence Nanjing Peoples R China

coverage is one of the basic problems that any wireless sensor network application must solve properly to achieve the expected quality of service. The communication distance of wireless sensor network nodes is limited, the initial energy is low, and many optimization objectives need to be considered in the deployment, which makes the network deployment optimization very complicated, and many problems are difficult. In essence, the deployment problem is a multidimensional nonlinear optimization problem with continuous discrete variables. In order to meet the needs of network monitoring, this article establishes a reasonable mathematical model according to the research objectives. By adjusting node position to obtain better network coverage effect, an optimization algorithm of monitoring area coverage based on control node position is proposed. By calculating the new location of nodes, more monitoring areas can be covered by the nodes. The simulation results show that the proposed algorithm can improve the coverage effect rapidly.

关键词： coverage optimization nodes position wireless sensor networks

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The coverage optimization Method for Underwater Sensor Network Based on VF-PSO Algorithm 32

The Coverage Optimization Method for Underwater Sensor Netwo...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Sun, Yujiao Hu, Yifan Chen, Lu Liu, Hailin Chen, Jie Lv, Bin Qilu Univ Technol Inst Oceanog Instrumentat Shandong Acad Sci Qingdao Peoples R China Shandong Prov Key Lab Ocean Environm Monitoring T Qingdao Peoples R China Natl Engn & Technol Res Ctr Marine Monitoring Equ Qingdao Peoples R China

ISBN: (纸本)9781728158556

coverage is an important indicator of the quality of underwater sensor network (UWSN) service. It reflects the monitoring capability of the network nodes to the UWSN deployment area and determines the overall lifetime of the UWSN. In order to improve network coverage and prolong network lifetime, this paper proposed a combination algorithm of virtual three and particle swarm optimization (VF-PSO). By the action of the virtual force, the underwater mobile nodes are moved to a relatively ideal position to maximize the network coverage. The virtual three is used to guide the optimization of the particle swarm so as to speed up the convergence of the particles to the global optimal solution. This algorithm not only effectively solves the problem of insufficient optimization ability of the virtual force algorithm, but also makes the particle swarm algorithm evolve towards the target solution that maximizes the area coverage. Simulation results show that the VF-PSO algorithm can effectively improve the effective coverage of underwater monitoring area, and avoid void-hole problem, while ensuring network connectivity compared with the algorithm proposed earlier.

关键词： Underwater sensor network VF-PSO algorithm coverage optimization Void hole

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WSN coverage optimization Based on Improved Lion Swarm optimization Algorithm

WSN Coverage Optimization Based on Improved Lion Swarm Optim...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Jiang, Keqin Jiang, Mingyan Song, Yucan Yuan, Dongfeng Shandong Univ Sch Informat Sci & Engn Qingdao Peoples R China Shandong Univ Shandong Key Lab Wireless Commun Technol Jinan Peoples R China

ISBN: (纸本)9798350377675;9798350377682

After the random deployment of wireless sensor nodes, issues such as overlapping coverage and detection blind spots inevitably arise. Employing intelligent optimization algorithms to optimize node deployment and expand network coverage is a common approach. However, the high-dimensional optimization problem of sensor node deployment and the complexity of coverage areas make it difficult for conventional intelligent optimization algorithms to achieve satisfactory solutions. To address these challenges, this paper proposes a wireless sensor network coverage optimization scheme based on a Lion Swarm optimization (LSO) algorithm with a crisscross strategy. By introducing both horizontal and vertical crisscrosses of individuals during the population evolution process, the diversity of the population is increased, enhancing the algorithm's global search capability and ability to escape local optima. Results demonstrate that the improved LSO algorithm exhibits enhanced solution accuracy and convergence compared to the standard LSO algorithm. In the context of wireless sensor network coverage optimization, this algorithm provides a better design solution.

关键词： wireless sensor network coverage optimization crisscross strategy improved Lion Swarm optimization algorithm

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Adaptive Antenna Tilt for Cellular coverage optimization in Suburban Scenario

Adaptive Antenna Tilt for Cellular Coverage Optimization in ...

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International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM)

作者： Samal, Soumya Ranjan Dandanov, Nikolay Bandopadhaya, Shuvabrata Poulkov, Vladimir Tech Univ Sofia Fac Telecommun Sofia Bulgaria BML Munjal Univ Gurgaon India

ISBN: (纸本)9783030390334;9783030390327

Radio coverage optimization is a critical issue for mobile network operators (MNO) in the deployment of future generation cellular networks, especially on users at cell edge. The key factor that influences the coverage in mobile networks is mostly related to the configuration of the antennas and especially the angle of antenna tilt. The received signal power in a cell can be increased with proper antenna tilt, causing a significant improvement in signal-to-interference-plus-noise ratio (SINR) at the cell edge. This also leads to reduction in interference towards other cells. In this paper, a method for coverage optimization using base station antenna electrical tilt in mobile networks for suburban scenario is proposed. The main focus is on the downlink power setting by using electrical antenna tilt in the mobile network. This proposed solution uses reinforcement learning technique and the simulation results shows that the proposed algorithm can used to improve overall network performance in terms of SINR and received signal power at the cell edge with 80-100% user satisfaction. The simulation has carried out by considering a multi-cell and three sector cellular networks in a suburban scenario where the users are randomly distributed.

关键词： Self-organizing networks (SON) coverage optimization Antenna tilt angle Reinforcement learning Cell edge users

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Testing AGV Mobility Control Method for MANET coverage optimization using Procedural Generation 21

Testing AGV Mobility Control Method for MANET Coverage Optim...

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24th International Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems

作者： Sauer, Christian Lyczkowski, Eike Schmidt, Marco Nuchter, Andreas Hassfeld, Tobias SEW EURODRIVE GmbH&Co KG Bruchsal Germany Univ Appl Sci Wiirzburg Schweinfurt Schweinfurt Germany Julius Maximilians Univ Wurzburg Germany

ISBN: (纸本)9781450390774

In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and adaptive positioning systems can reduce the number of disconnections in these AGV fleets. Therefore the performance of the mobile systems (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This methods enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.

关键词： Mobile Ad-hoc Network Mobile Robotics Industrial Application coverage optimization Procedural Generation

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The coverage optimization for Wireless Sensor Networks Based on Quantum-Inspired Cultural Algorithm 1

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Chinese Intelligent Automation Conference (CIAC)

作者： Guo, Yi-nan Liu, Dandan Liu, Yun Chen, Meirong China Univ Min & Technol Coll Informat & Elect Engn Xuzhou 221116 Jiangsu Peoples R China

ISBN: (数字)9783642385247

ISBN: (纸本)9783642385247;9783642385230

In order to properly distribute sensor nodes in wireless sensor networks, a coverage model considering maximum coverage ratio and minimum redundancy is given and the optimization strategy based on quantum-inspired cultural algorithm is proposed. In population space, quantum-inspired evolutionary algorithm is used to increase the observed probability. In belief space, the implicit knowledge embodied in the evolution is extracted from the better individuals chosen from the population. It is used to guide the search direction of evolutionary population and influence the update of quantum individuals. Simulation results indicate that the algorithm is superior to other algorithms in coverage optimization and effectively improve the coverage performance of wireless sensor networks.

关键词： Wireless sensor networks Quantum-inspired algorithm Cultural algorithm coverage optimization

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AUTOMS: Automated Service for mmWave coverage optimization using Low-cost Metasurfaces 24

AUTOMS: Automated Service for mmWave Coverage Optimization u...

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30th International Conference on Mobile Computing and Networking (ACM MobiCom)

作者： Ma, Ruichun Zheng, Shicheng Pan, Hao Qiu, Lili Chen, Xingyu Liu, Liangyu Liu, Yihong Hu, Wenjun Ren, Ju Yale Univ New Haven CT 06520 USA Univ Sci & Technol China Hefei Peoples R China Microsoft Res Asia Beijing Peoples R China UT Austin Austin TX USA Univ Calif San Diego San Diego CA 92103 USA Univ Glasgow Glasgow Lanark Scotland Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9798400704895

mmWave networks offer wide bandwidth for high-speed wireless communication but suffer from limited range and susceptibility to blockage. Existing coverage provisioning solutions not only incur high costs but also require significant expert knowledge and manual efforts. In this paper, we present AUTOMS, an automated service framework to optimize mmWave coverage by strategically designing and placing low-cost passive metasurfaces. Our approach consists of three key components: (1) joint optimization of metasurface phase configurations and placement as well as access point beamforming codebooks. (2) a fast 3D ray-tracing simulator for accelerated large-scale metasurface channel modeling. (3) a metasurface design amenable to ultra-low-cost hot stamping fabrication, featuring high reflectivity, near 2 pi phase control, and wideband support. Simulation and testbed experiments show that AUTOMS can increase the median received signal strength by 11 dB in target rooms and over 20 dB at previous blind spots, and improve the median throughput by over 3x in real-world scenarios.

关键词： Millimeter-wave coverage optimization Cloud service Metasurfaces Ray-tracing simulator

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Optical Power coverage optimization for UAV-enabled Visible Light Communication

Optical Power Coverage Optimization for UAV-enabled Visible ...

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IEEE International Conference on Communications (ICC)

作者： Liu, Yanheng Lu, Jiao Sun, Geng Liu, Lingling Zhang, Jiayun Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

Visible light communication (VLC) based on un-manned aerial vehicles (UAVs) can simultaneously transmit data and lighting, which has been considered as a promising technology for the next generation wireless networks. In this paper, we construct a system consisting of UAV elements to fairly communicate with receiving plane. However, the unreasonable layout of UAVs may lead to the uneven distribution of the received optical power on the same receiving plane, which cannot guarantee the fairness of the communication between the UAVs and receiving plane. Besides, the transmission power of the UAVs has direct effects on the strength of the received optical signal in VLC communication. Therefore, we formulate an optical power coverage optimization problem (OPCOP) to achieve more uniform received optical power coverage by jointly considering the positions and appropriate power adjustment factor of transmission power of UAVs. Then, an improved cuckoo search with chaotic solution initialization operation and mutation mechanisms (ICSCM) algorithm is proposed to solve the formulated optimization problem. ICSCM introduces the chaotic solution initialization operation for increasing the performance of initial solution, and employs two mutation mechanisms, which are mutation operator of differential evolution (DE) algorithm and Gaussian perturbation to enhance the exploration ability of conventional cuckoo search (CS). Simulations are conducted and the results verify that the received optical power of receivers distributed on the same receiving plane obtained by ICSCM can be more uniform than other comparison methods.

关键词： Unmanned aerial vehicles visible light communication coverage optimization cuckoo search

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