{"title":"移动环境中的功率感知预取","authors":"Liangzhong Yin, G. Cao, C. Das, A. Ashraf","doi":"10.1109/ICDCS.2002.1022307","DOIUrl":null,"url":null,"abstract":"Most of the prefetch techniques used in the current cache management schemes do not consider the power constraints of the mobile clients and other factors such as the size of the data items, the data access rate, and the data update rate. We address these issues by proposing a power-aware prefetch scheme, called the value-based adaptive prefetch (VAP) scheme. The VAP scheme defines a value function which can optimize the prefetch cost to achieve better performance. Also, VAP dynamically adjusts the number of prefetches based on the current energy level to prolong the system running time. As stretch is widely adopted as a performance metric for variable-size data requests, we show by analysis that the proposed algorithm can indeed achieve the optimal performance in terms of stretch when power consumption is considered. Simulation results demonstrate that our algorithm significantly outperforms existing prefetching algorithms under various scenarios.","PeriodicalId":186210,"journal":{"name":"Proceedings 22nd International Conference on Distributed Computing Systems","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":"{\"title\":\"Power-aware prefetch in mobile environments\",\"authors\":\"Liangzhong Yin, G. Cao, C. Das, A. Ashraf\",\"doi\":\"10.1109/ICDCS.2002.1022307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most of the prefetch techniques used in the current cache management schemes do not consider the power constraints of the mobile clients and other factors such as the size of the data items, the data access rate, and the data update rate. We address these issues by proposing a power-aware prefetch scheme, called the value-based adaptive prefetch (VAP) scheme. The VAP scheme defines a value function which can optimize the prefetch cost to achieve better performance. Also, VAP dynamically adjusts the number of prefetches based on the current energy level to prolong the system running time. As stretch is widely adopted as a performance metric for variable-size data requests, we show by analysis that the proposed algorithm can indeed achieve the optimal performance in terms of stretch when power consumption is considered. Simulation results demonstrate that our algorithm significantly outperforms existing prefetching algorithms under various scenarios.\",\"PeriodicalId\":186210,\"journal\":{\"name\":\"Proceedings 22nd International Conference on Distributed Computing Systems\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 22nd International Conference on Distributed Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCS.2002.1022307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 22nd International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2002.1022307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Most of the prefetch techniques used in the current cache management schemes do not consider the power constraints of the mobile clients and other factors such as the size of the data items, the data access rate, and the data update rate. We address these issues by proposing a power-aware prefetch scheme, called the value-based adaptive prefetch (VAP) scheme. The VAP scheme defines a value function which can optimize the prefetch cost to achieve better performance. Also, VAP dynamically adjusts the number of prefetches based on the current energy level to prolong the system running time. As stretch is widely adopted as a performance metric for variable-size data requests, we show by analysis that the proposed algorithm can indeed achieve the optimal performance in terms of stretch when power consumption is considered. Simulation results demonstrate that our algorithm significantly outperforms existing prefetching algorithms under various scenarios.