OPTIMIZING DATA DISTRIBUTION IN DESKTOP GRID PLATFORMS

Abstract

Current infrastructures for Volunteer Computing follow a centralized architecture for data distribution, creating a potential bottleneck when tasks require large input files or the central server has limited bandwidth. In this paper we propose two new data models for Berkeley Open Infrastructure for Network Computing (BOINC): an approach based on the popular BitTorrent protocol; and a Content Delivery Network approach. While the latter remains on a theoretical level, we developed a prototype that adds BitTorrent functionality for task distribution and conducted medium-scale tests of the environment. Our preliminary results indicate that the BitTorrent client had a negligible influence on the BOINC client's computation time. The BOINC server showed an unexpectedly low bandwidth output when seeding the file, as well as spikes on CPU usage. This paper discusses the tests that were performed, how they were evaluated, as well as some improvements that could be made in future research on both approaches.