{"title":"分析以人为中心的数据,与社交伙伴共享移动互联网","authors":"S. Gurumurthy, A. Ganz","doi":"10.1109/CCNC.2009.4784864","DOIUrl":null,"url":null,"abstract":"We propose a middleware called BuddyShare to automatically form an overlay group of nearby friends' mobile phones to collaboratively download data by sharing mobile internet. This system is hypothetical in nature and only work on certain assumptions such as: 1) frequent availability of friends' phone nearby, 2) Sufficient social trust among physically close users to share internet and 3) sufficient social networking information available in phones. In order to validate these hypotheses, we collected human centric dataset of cellular phone users of university environment to study the user behavior. In this paper, we present certain social and proximity behaviors of these users that validate these hypotheses and show the practical feasibility of a BuddyShare system. We also study the usefulness of BuddyShare by virtually leveraging it on this user network, which concludes around three times scaling in download rate on average.","PeriodicalId":181188,"journal":{"name":"2009 6th IEEE Consumer Communications and Networking Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing Human Centric Data for Sharing Mobile Internet with Social Buddies\",\"authors\":\"S. Gurumurthy, A. Ganz\",\"doi\":\"10.1109/CCNC.2009.4784864\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a middleware called BuddyShare to automatically form an overlay group of nearby friends' mobile phones to collaboratively download data by sharing mobile internet. This system is hypothetical in nature and only work on certain assumptions such as: 1) frequent availability of friends' phone nearby, 2) Sufficient social trust among physically close users to share internet and 3) sufficient social networking information available in phones. In order to validate these hypotheses, we collected human centric dataset of cellular phone users of university environment to study the user behavior. In this paper, we present certain social and proximity behaviors of these users that validate these hypotheses and show the practical feasibility of a BuddyShare system. We also study the usefulness of BuddyShare by virtually leveraging it on this user network, which concludes around three times scaling in download rate on average.\",\"PeriodicalId\":181188,\"journal\":{\"name\":\"2009 6th IEEE Consumer Communications and Networking Conference\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 6th IEEE Consumer Communications and Networking Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCNC.2009.4784864\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 6th IEEE Consumer Communications and Networking Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2009.4784864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing Human Centric Data for Sharing Mobile Internet with Social Buddies
We propose a middleware called BuddyShare to automatically form an overlay group of nearby friends' mobile phones to collaboratively download data by sharing mobile internet. This system is hypothetical in nature and only work on certain assumptions such as: 1) frequent availability of friends' phone nearby, 2) Sufficient social trust among physically close users to share internet and 3) sufficient social networking information available in phones. In order to validate these hypotheses, we collected human centric dataset of cellular phone users of university environment to study the user behavior. In this paper, we present certain social and proximity behaviors of these users that validate these hypotheses and show the practical feasibility of a BuddyShare system. We also study the usefulness of BuddyShare by virtually leveraging it on this user network, which concludes around three times scaling in download rate on average.