{"title":"CSN 中基于动态时间窗口的全视角覆盖最大化","authors":"Jingfang Su, Zeqing Li, Hongwei Du, Shengxin Liu","doi":"10.1007/s10878-024-01227-6","DOIUrl":null,"url":null,"abstract":"<p>In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2<span>\\(\\pi \\)</span>], use a set of views of targets to represent the sensing direction of the camera sensor, and use a group set of views of targets to represent the position of the camera sensor. The total number of targets in a dynamic time window that is visible in full view is calculated. A mixed integer linear programming formulation is employed, which is then approximated using a random rounding method. This approximation approach offers a global estimation of local optimality, particularly for non-submodular optimization problems. Two methods for maximizing overall full-view coverage within a dynamic time window are proposed TSC-FTC-DTW and FTC-TW-DTW. Finally, the proposed methods are verified through experiments.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"2 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic time window based full-view coverage maximization in CSNs\",\"authors\":\"Jingfang Su, Zeqing Li, Hongwei Du, Shengxin Liu\",\"doi\":\"10.1007/s10878-024-01227-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2<span>\\\\(\\\\pi \\\\)</span>], use a set of views of targets to represent the sensing direction of the camera sensor, and use a group set of views of targets to represent the position of the camera sensor. The total number of targets in a dynamic time window that is visible in full view is calculated. A mixed integer linear programming formulation is employed, which is then approximated using a random rounding method. This approximation approach offers a global estimation of local optimality, particularly for non-submodular optimization problems. Two methods for maximizing overall full-view coverage within a dynamic time window are proposed TSC-FTC-DTW and FTC-TW-DTW. Finally, the proposed methods are verified through experiments.</p>\",\"PeriodicalId\":50231,\"journal\":{\"name\":\"Journal of Combinatorial Optimization\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Combinatorial Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10878-024-01227-6\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-024-01227-6","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Dynamic time window based full-view coverage maximization in CSNs
In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2\(\pi \)], use a set of views of targets to represent the sensing direction of the camera sensor, and use a group set of views of targets to represent the position of the camera sensor. The total number of targets in a dynamic time window that is visible in full view is calculated. A mixed integer linear programming formulation is employed, which is then approximated using a random rounding method. This approximation approach offers a global estimation of local optimality, particularly for non-submodular optimization problems. Two methods for maximizing overall full-view coverage within a dynamic time window are proposed TSC-FTC-DTW and FTC-TW-DTW. Finally, the proposed methods are verified through experiments.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.