Internet-scale support for map-reduce processing

Abstract

Volunteer Computing systems (VC) harness computing resources of machines from around the world to perform distributed independent tasks. Existing infrastructures follow a master/worker model, with a centralized architecture. This limits the scalability of the solution due to its dependence on the server. Our goal is to create a fault-tolerant VC platform that supports complex applications, by using a distributed model which improves performance and reduces the burden on the server. In this paper we present VMR, a VC system able to run MapReduce applications on top of volunteer resources, spread throughout the Internet. VMR leverages users’ bandwidth through the use of inter-client communication, and uses a lightweight task validation mechanism. We describe VMR’s architecture and evaluate its performance by executing several MapReduce applications on a wide area testbed. Our results show that VMR successfully runs MapReduce tasks over the Internet. When compared to an unmodified VC system, VMR obtains a performance increase of over 60% in application turnaround time, while reducing server bandwidth use by two orders of magnitude and showing no discernible overhead.