{"title":"利用Voronoi图改善方向传感器网络的覆盖范围","authors":"Zahra Zarei, Mozafar Bag-Mohammadi","doi":"10.1049/wss2.12015","DOIUrl":null,"url":null,"abstract":"<p>Recently, the area coverage problem has emerged in the directional sensor network (DSN), where the sensor's sensed area depends on its working direction and viewing angle. This study has proposed a new algorithm based on the Voronoi diagram, called prioritized geometric area coverage (PGAC), to increase DSN's covered area. In a Voronoi diagram, all internal points of a convex polygon (cell) formed around a sensor are closer to the sensor than any other sensor. Therefore, the best sensor for covering a Voronoi cell area is the corresponding sensor of the cell. In contrast to similar approaches, PGAC considers the relation between the cell area and the sensor's covered area when selecting a sensor's working direction. It categorizes Voronoi cells, based on their geometric sizes, into three categories. In each category, PGAC adjusts the sensor's working direction to maximize the covered area and minimize the overlapping between adjacent cells. It also turns off redundant sensors for extending the network lifetime. Our simulation results showed that PGAC increases the covered area and decreases the number of active sensors compared to similar methods.</p>","PeriodicalId":51726,"journal":{"name":"IET Wireless Sensor Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12015","citationCount":"4","resultStr":"{\"title\":\"Coverage improvement using Voronoi diagrams in directional sensor networks\",\"authors\":\"Zahra Zarei, Mozafar Bag-Mohammadi\",\"doi\":\"10.1049/wss2.12015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Recently, the area coverage problem has emerged in the directional sensor network (DSN), where the sensor's sensed area depends on its working direction and viewing angle. This study has proposed a new algorithm based on the Voronoi diagram, called prioritized geometric area coverage (PGAC), to increase DSN's covered area. In a Voronoi diagram, all internal points of a convex polygon (cell) formed around a sensor are closer to the sensor than any other sensor. Therefore, the best sensor for covering a Voronoi cell area is the corresponding sensor of the cell. In contrast to similar approaches, PGAC considers the relation between the cell area and the sensor's covered area when selecting a sensor's working direction. It categorizes Voronoi cells, based on their geometric sizes, into three categories. In each category, PGAC adjusts the sensor's working direction to maximize the covered area and minimize the overlapping between adjacent cells. It also turns off redundant sensors for extending the network lifetime. Our simulation results showed that PGAC increases the covered area and decreases the number of active sensors compared to similar methods.</p>\",\"PeriodicalId\":51726,\"journal\":{\"name\":\"IET Wireless Sensor Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/wss2.12015\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Wireless Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/wss2.12015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Wireless Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/wss2.12015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Coverage improvement using Voronoi diagrams in directional sensor networks
Recently, the area coverage problem has emerged in the directional sensor network (DSN), where the sensor's sensed area depends on its working direction and viewing angle. This study has proposed a new algorithm based on the Voronoi diagram, called prioritized geometric area coverage (PGAC), to increase DSN's covered area. In a Voronoi diagram, all internal points of a convex polygon (cell) formed around a sensor are closer to the sensor than any other sensor. Therefore, the best sensor for covering a Voronoi cell area is the corresponding sensor of the cell. In contrast to similar approaches, PGAC considers the relation between the cell area and the sensor's covered area when selecting a sensor's working direction. It categorizes Voronoi cells, based on their geometric sizes, into three categories. In each category, PGAC adjusts the sensor's working direction to maximize the covered area and minimize the overlapping between adjacent cells. It also turns off redundant sensors for extending the network lifetime. Our simulation results showed that PGAC increases the covered area and decreases the number of active sensors compared to similar methods.
期刊介绍:
IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.