Angels in the Cloud: A Peer-Assisted Bulk-Synchronous Content Distribution Service

Leveraging client upload capacity through peer assisted content distribution was shown to decrease the load on content providers, while also improving average distribution times. These benefits, however, are limited by the disparity between client upload and download speeds, especially in scenarios requiring a minimum distribution time (MDT) of a fresh piece of content to a set of clients. Achieving MDT is crucial for bulk-synchronous applications, when every client in a set must wait for all other clients in the set to finish their downloads before being able to make use of the downloaded content. In this paper, we propose the use of dedicated servers, which we call angels to accelerate peer-assisted content distribution in general, and to minimize MDT in particular. An angel is not itself the content origin, nor is it interested in fully downloading the content, its only purpose is to enable a peer assisted content distribution scheme to approach the theoretical lower-bound for MDT. To overcome scalability issues inherent in an optimal MDT construction, we propose and evaluate a content exchange strategy involving angels, which we call Group Tree. In addition to simulation results that demonstrate the near optimal performance of our proposed approach, we present the architecture and implementation of CLOUDANGELS -- a service that allows the elastic, on-the-fly deployment of angels (in the cloud) to assist a content provider (off the cloud) in realizing its MDT objective.