{"title":"基于移动单元(ME)的无线传感器网络数据采集的整数线性表述方案","authors":"Sujeet Kumar, R. Chaudhary, A. Deepak, D. Dash","doi":"10.1109/WOCN.2016.7759892","DOIUrl":null,"url":null,"abstract":"Nowadays wireless sensor network (WSN) plays an important role in every field of technology. Data collection is a major issue in WSN because the data has to be collected in a way that maximizes life time of WSN, minimizes the energy consumption and gives shortest path in case of mobile sinks. In this paper we divide the whole network into grids. Certain grids are critical (e.g., during a terror strike) in the sense that (a) it may not be possible for mobile elements to enter those grids, and (b) the sensor nodes in those grids are required to sense data at a higher rate due to the critically in the their surrounding environment. A subset of sensor nodes are designated as cache points such that each sensor node must deliver its sensed data to one of the cache points. Now the mobile movable sink has to make a tour schedule and visit each cache point exactly once such that it is able to collect data from all cache points in due time without causing buffer overflow at any of the cache points. We divide the problem into two parts. In the first part, we find cache points such that no cache point is also a critical sensor node and the energy consumption by critical nodes is minimized. In the second part, we find the shortest path among the caches points from the first step. Both problems are known to be NP-Complete and here we give ILP formulations for them.","PeriodicalId":234041,"journal":{"name":"2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An integer linear formulation scheme for data collection in wireless sensor network using mobile element (ME)\",\"authors\":\"Sujeet Kumar, R. Chaudhary, A. Deepak, D. Dash\",\"doi\":\"10.1109/WOCN.2016.7759892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays wireless sensor network (WSN) plays an important role in every field of technology. Data collection is a major issue in WSN because the data has to be collected in a way that maximizes life time of WSN, minimizes the energy consumption and gives shortest path in case of mobile sinks. In this paper we divide the whole network into grids. Certain grids are critical (e.g., during a terror strike) in the sense that (a) it may not be possible for mobile elements to enter those grids, and (b) the sensor nodes in those grids are required to sense data at a higher rate due to the critically in the their surrounding environment. A subset of sensor nodes are designated as cache points such that each sensor node must deliver its sensed data to one of the cache points. Now the mobile movable sink has to make a tour schedule and visit each cache point exactly once such that it is able to collect data from all cache points in due time without causing buffer overflow at any of the cache points. We divide the problem into two parts. In the first part, we find cache points such that no cache point is also a critical sensor node and the energy consumption by critical nodes is minimized. In the second part, we find the shortest path among the caches points from the first step. Both problems are known to be NP-Complete and here we give ILP formulations for them.\",\"PeriodicalId\":234041,\"journal\":{\"name\":\"2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOCN.2016.7759892\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCN.2016.7759892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An integer linear formulation scheme for data collection in wireless sensor network using mobile element (ME)
Nowadays wireless sensor network (WSN) plays an important role in every field of technology. Data collection is a major issue in WSN because the data has to be collected in a way that maximizes life time of WSN, minimizes the energy consumption and gives shortest path in case of mobile sinks. In this paper we divide the whole network into grids. Certain grids are critical (e.g., during a terror strike) in the sense that (a) it may not be possible for mobile elements to enter those grids, and (b) the sensor nodes in those grids are required to sense data at a higher rate due to the critically in the their surrounding environment. A subset of sensor nodes are designated as cache points such that each sensor node must deliver its sensed data to one of the cache points. Now the mobile movable sink has to make a tour schedule and visit each cache point exactly once such that it is able to collect data from all cache points in due time without causing buffer overflow at any of the cache points. We divide the problem into two parts. In the first part, we find cache points such that no cache point is also a critical sensor node and the energy consumption by critical nodes is minimized. In the second part, we find the shortest path among the caches points from the first step. Both problems are known to be NP-Complete and here we give ILP formulations for them.