{"title":"基于蓝牙微网节能的嗅探调度策略","authors":"Xiang Li, Xiaozong Yang","doi":"10.1109/ICPADS.2005.52","DOIUrl":null,"url":null,"abstract":"After deeply analyzing sniff mode which is a low power operation mode of Bluetooth, a learning function is used to approximate the distribution of the incoming traffic at a master-slave pair. Based the inter-arrival times of data packets obtained from the learning function, the mean of these inter-arrival times is the possible sniff interval; according to the backlog packets in the buffer space and forecast next burst data traffic, a cost model is used to approximate the slot occupancy assigned to a slave. Consequently, calculate sniff attempt slots, and go into sniff mode if conditions are satisfied. Finally, computer simulation results validate that the proposed scheduling policy can save about 38.6% power consumption compared to the always active mode.","PeriodicalId":281075,"journal":{"name":"International Conference on Parallel and Distributed Systems","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Sniff Scheduling Policy for Power Saving in Bluetooth Piconet\",\"authors\":\"Xiang Li, Xiaozong Yang\",\"doi\":\"10.1109/ICPADS.2005.52\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"After deeply analyzing sniff mode which is a low power operation mode of Bluetooth, a learning function is used to approximate the distribution of the incoming traffic at a master-slave pair. Based the inter-arrival times of data packets obtained from the learning function, the mean of these inter-arrival times is the possible sniff interval; according to the backlog packets in the buffer space and forecast next burst data traffic, a cost model is used to approximate the slot occupancy assigned to a slave. Consequently, calculate sniff attempt slots, and go into sniff mode if conditions are satisfied. Finally, computer simulation results validate that the proposed scheduling policy can save about 38.6% power consumption compared to the always active mode.\",\"PeriodicalId\":281075,\"journal\":{\"name\":\"International Conference on Parallel and Distributed Systems\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Parallel and Distributed Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPADS.2005.52\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Parallel and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPADS.2005.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Sniff Scheduling Policy for Power Saving in Bluetooth Piconet
After deeply analyzing sniff mode which is a low power operation mode of Bluetooth, a learning function is used to approximate the distribution of the incoming traffic at a master-slave pair. Based the inter-arrival times of data packets obtained from the learning function, the mean of these inter-arrival times is the possible sniff interval; according to the backlog packets in the buffer space and forecast next burst data traffic, a cost model is used to approximate the slot occupancy assigned to a slave. Consequently, calculate sniff attempt slots, and go into sniff mode if conditions are satisfied. Finally, computer simulation results validate that the proposed scheduling policy can save about 38.6% power consumption compared to the always active mode.