{"title":"无线传感器和机器人网络中基于载波的覆盖增强","authors":"R. Falcon, Xu Li, A. Nayak","doi":"10.1109/ICDCSW.2010.60","DOIUrl":null,"url":null,"abstract":"Carrier-based sensor placement involves mobile robots carrying and dropping (static) sensors for optimal coverage formation. Existing solutions target at traditional area coverage problem and unrealistically assume that robots carry sensors all together (ignoring the physical dimension of sensors and the limit of robot capacity). In this paper, we consider realistic scenarios that robots have to repeatedly reload sensors and address the FOCUSED coverage (F-coverage) problem [10]in an unknown two-dimensional environment. In F-coverage, sensors are required to surround a point of interest (POI), maximizing coverage radius. We propose a Carrier-Based Coverage Augmentation protocol (CBCA). Robots enter the environment from fixed locations, called base points, and move toward the POI. As soon as they get in touch with already deployed sensors, they search (by communication) along the network border for best sensor placement points with respect to F-coverage optimization, and move to drop sensors at the discovered locations. Border nodes store locations of failed sensors (if any exists) inside the network as well as adjacent available deployment spots outside the network, and recommend them to robots during the search process. Robots return to base points for reloading, after finishing with currently loaded sensors, and re-enter the environment to augment existing F-coverage. At the end o the paper, we propose an optimization technique to reduce augmentation delay and save robot energy.","PeriodicalId":133907,"journal":{"name":"2010 IEEE 30th International Conference on Distributed Computing Systems Workshops","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Carrier-Based Coverage Augmentation in Wireless Sensor and Robot Networks\",\"authors\":\"R. Falcon, Xu Li, A. Nayak\",\"doi\":\"10.1109/ICDCSW.2010.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Carrier-based sensor placement involves mobile robots carrying and dropping (static) sensors for optimal coverage formation. Existing solutions target at traditional area coverage problem and unrealistically assume that robots carry sensors all together (ignoring the physical dimension of sensors and the limit of robot capacity). In this paper, we consider realistic scenarios that robots have to repeatedly reload sensors and address the FOCUSED coverage (F-coverage) problem [10]in an unknown two-dimensional environment. In F-coverage, sensors are required to surround a point of interest (POI), maximizing coverage radius. We propose a Carrier-Based Coverage Augmentation protocol (CBCA). Robots enter the environment from fixed locations, called base points, and move toward the POI. As soon as they get in touch with already deployed sensors, they search (by communication) along the network border for best sensor placement points with respect to F-coverage optimization, and move to drop sensors at the discovered locations. Border nodes store locations of failed sensors (if any exists) inside the network as well as adjacent available deployment spots outside the network, and recommend them to robots during the search process. Robots return to base points for reloading, after finishing with currently loaded sensors, and re-enter the environment to augment existing F-coverage. At the end o the paper, we propose an optimization technique to reduce augmentation delay and save robot energy.\",\"PeriodicalId\":133907,\"journal\":{\"name\":\"2010 IEEE 30th International Conference on Distributed Computing Systems Workshops\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 30th International Conference on Distributed Computing Systems Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCSW.2010.60\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 30th International Conference on Distributed Computing Systems Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCSW.2010.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Carrier-Based Coverage Augmentation in Wireless Sensor and Robot Networks
Carrier-based sensor placement involves mobile robots carrying and dropping (static) sensors for optimal coverage formation. Existing solutions target at traditional area coverage problem and unrealistically assume that robots carry sensors all together (ignoring the physical dimension of sensors and the limit of robot capacity). In this paper, we consider realistic scenarios that robots have to repeatedly reload sensors and address the FOCUSED coverage (F-coverage) problem [10]in an unknown two-dimensional environment. In F-coverage, sensors are required to surround a point of interest (POI), maximizing coverage radius. We propose a Carrier-Based Coverage Augmentation protocol (CBCA). Robots enter the environment from fixed locations, called base points, and move toward the POI. As soon as they get in touch with already deployed sensors, they search (by communication) along the network border for best sensor placement points with respect to F-coverage optimization, and move to drop sensors at the discovered locations. Border nodes store locations of failed sensors (if any exists) inside the network as well as adjacent available deployment spots outside the network, and recommend them to robots during the search process. Robots return to base points for reloading, after finishing with currently loaded sensors, and re-enter the environment to augment existing F-coverage. At the end o the paper, we propose an optimization technique to reduce augmentation delay and save robot energy.