Yindi Yao;Xiaoxiao Song;Bozhan Zhao;Yuying Tian;Ying Yang;Maoduo Yang
{"title":"基于改进的北方大鹰算法的覆盖优化策略研究","authors":"Yindi Yao;Xiaoxiao Song;Bozhan Zhao;Yuying Tian;Ying Yang;Maoduo Yang","doi":"10.1109/JSEN.2024.3419174","DOIUrl":null,"url":null,"abstract":"To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research of Coverage Optimization Strategy Based on Improved Northern Goshawk Algorithm\",\"authors\":\"Yindi Yao;Xiaoxiao Song;Bozhan Zhao;Yuying Tian;Ying Yang;Maoduo Yang\",\"doi\":\"10.1109/JSEN.2024.3419174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability.\",\"PeriodicalId\":447,\"journal\":{\"name\":\"IEEE Sensors Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Journal\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10582836/\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10582836/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Research of Coverage Optimization Strategy Based on Improved Northern Goshawk Algorithm
To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice