{"title":"基于在线多网分组调度的高效移动数据传输","authors":"Aaron Cote, A. Meyerson, Brian Tagiku","doi":"10.1109/GREENCOMP.2010.5598312","DOIUrl":null,"url":null,"abstract":"We explore a novel online packet scheduling model related to energy-efficiency in mobile data transport. This model incorporates multiple networks with non-persistent connectivities where we only know which networks are available in the current timestep. When a packet arrives, it specifies a deadline and, for each network, a value it is worth if sent over that network. Our goal is to maximize the total value of packets we send by their deadlines. To encourage energy-efficiency, our model requires that packets have larger values for more energy-efficient networks. We demonstrate low-constant-competitive algorithms for this problem and several restrictions. We also provide lower bounds which closely match our competitive ratios and, under some restrictions, are tight.","PeriodicalId":262148,"journal":{"name":"International Conference on Green Computing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Energy-efficient mobile data transport via online multi-network packet scheduling\",\"authors\":\"Aaron Cote, A. Meyerson, Brian Tagiku\",\"doi\":\"10.1109/GREENCOMP.2010.5598312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore a novel online packet scheduling model related to energy-efficiency in mobile data transport. This model incorporates multiple networks with non-persistent connectivities where we only know which networks are available in the current timestep. When a packet arrives, it specifies a deadline and, for each network, a value it is worth if sent over that network. Our goal is to maximize the total value of packets we send by their deadlines. To encourage energy-efficiency, our model requires that packets have larger values for more energy-efficient networks. We demonstrate low-constant-competitive algorithms for this problem and several restrictions. We also provide lower bounds which closely match our competitive ratios and, under some restrictions, are tight.\",\"PeriodicalId\":262148,\"journal\":{\"name\":\"International Conference on Green Computing\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Green Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GREENCOMP.2010.5598312\",\"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 Green Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GREENCOMP.2010.5598312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy-efficient mobile data transport via online multi-network packet scheduling
We explore a novel online packet scheduling model related to energy-efficiency in mobile data transport. This model incorporates multiple networks with non-persistent connectivities where we only know which networks are available in the current timestep. When a packet arrives, it specifies a deadline and, for each network, a value it is worth if sent over that network. Our goal is to maximize the total value of packets we send by their deadlines. To encourage energy-efficiency, our model requires that packets have larger values for more energy-efficient networks. We demonstrate low-constant-competitive algorithms for this problem and several restrictions. We also provide lower bounds which closely match our competitive ratios and, under some restrictions, are tight.