VMR: volunteer MapReduce over the large scale internet

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, which limits the scalability of the solution given its dependence on the server. We intend to create a distributed model, in order to improve performance and reduce the burden on the server. In this paper we present VMR, a VC system able to run MapReduce applications on top of volunteer resources, over the large scale Internet. 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 the bandwidth use by an order of magnitude.