{"title":"通过移动预测和预取增强移动数据卸载","authors":"V. Siris, Dimitrios Kalyvas","doi":"10.1145/2348676.2348682","DOIUrl":null,"url":null,"abstract":"We present procedures that exploit mobility prediction and prefetching to enhance offloading of traffic from mobile networks to WiFi hotspots, for both delay tolerant and delay sensitive traffic. We evaluate the procedures in terms of the percentage of offloaded traffic, the data transfer delay, and the cache size used for prefetching. The evaluation considers empirical measurements and shows how various parameters influence the performance of the procedures, and their robustness to time and throughput estimation errors.","PeriodicalId":43578,"journal":{"name":"Mobile Computing and Communications Review","volume":"13 1","pages":"22-29"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Enhancing mobile data offloading with mobility prediction and prefetching\",\"authors\":\"V. Siris, Dimitrios Kalyvas\",\"doi\":\"10.1145/2348676.2348682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present procedures that exploit mobility prediction and prefetching to enhance offloading of traffic from mobile networks to WiFi hotspots, for both delay tolerant and delay sensitive traffic. We evaluate the procedures in terms of the percentage of offloaded traffic, the data transfer delay, and the cache size used for prefetching. The evaluation considers empirical measurements and shows how various parameters influence the performance of the procedures, and their robustness to time and throughput estimation errors.\",\"PeriodicalId\":43578,\"journal\":{\"name\":\"Mobile Computing and Communications Review\",\"volume\":\"13 1\",\"pages\":\"22-29\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mobile Computing and Communications Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2348676.2348682\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mobile Computing and Communications Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2348676.2348682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing mobile data offloading with mobility prediction and prefetching
We present procedures that exploit mobility prediction and prefetching to enhance offloading of traffic from mobile networks to WiFi hotspots, for both delay tolerant and delay sensitive traffic. We evaluate the procedures in terms of the percentage of offloaded traffic, the data transfer delay, and the cache size used for prefetching. The evaluation considers empirical measurements and shows how various parameters influence the performance of the procedures, and their robustness to time and throughput estimation errors.