{"title":"基于流体模型的P2P文件共享应用中的建模搜索、可用性和并行下载","authors":"D. Manini, M. Gribaudo","doi":"10.1109/ADCOM.2006.4289934","DOIUrl":null,"url":null,"abstract":"File transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations file transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations.","PeriodicalId":296627,"journal":{"name":"2006 International Conference on Advanced Computing and Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Modelling Search, Availability, and Parallel Download in P2P File Sharing Applications with Fluid Model\",\"authors\":\"D. Manini, M. Gribaudo\",\"doi\":\"10.1109/ADCOM.2006.4289934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"File transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations file transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations.\",\"PeriodicalId\":296627,\"journal\":{\"name\":\"2006 International Conference on Advanced Computing and Communications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Advanced Computing and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ADCOM.2006.4289934\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Advanced Computing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ADCOM.2006.4289934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelling Search, Availability, and Parallel Download in P2P File Sharing Applications with Fluid Model
File transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations file transfer using peer-to-peer file sharing applications is usually divided into two steps: resource search and resource download. Depending on the file size and its popularity, either of the two phases can become the bottleneck. In this paper we describe both the location and download phases of a generic peer-to-peer file sharing application using a fluid model. The proposed model allows the computation of the transfer time distribution, and it is capable of considering some advanced characteristic such as parallel downloads and on-off peer behavior. Model parameters reflect network, application, resource and user characteristics, and can be tuned to analyze a large number of different real peer-to-peer implementations.