Improving the Performance of Volunteer Computing with Data Volunteers: A Case Study with the ATLAS@home Project

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• 关键词：BOINC ; Data volunteers ; Throughput ; Simulation ; Volunteer computing
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：10048
• 期：1
• 页码：178-191
• 丛书名：Algorithms and Architectures for Parallel Processing
• ISBN：978-3-319-49583-5
• 卷排序：10048

文摘

Volunteer computing is a type of distributed computing in which ordinary people donate processing and storage resources to scientific projects. BOINC is the main middleware system for this type of computing. The aim of volunteer computing is that organizations be able to attain large computing power thanks to the participation of volunteer clients instead of a high investment in infrastructure. There are projects, like the ATLAS@home project, in which the number of running jobs has reached a plateau, due to a high load on data servers caused by file transfer. This is why we have designed an alternative, using the same BOINC infrastructure, in order to improve the performance of BOINC projects that have reached their physical limit. This alternative involves having a percentage of the volunteer clients running as data servers, called data volunteers, that improve the performance by reducing the load on data servers. This paper describes our alternative in detail and shows the performance of the solution using a simulator of our own, ComBoS.