Cloud-based Content Distribution on a Budget

To leverage the elastic nature of cloud computing, a solution provider must be able to accurately gauge demand for its offering. For applications that involve swarm-to-cloud interactions, gauging such demand is not straightforward. In this paper, we propose a general framework, analyze a mathematical model, and present a prototype implementation of a canonical swarm-to-cloud application, namely peer-assisted content delivery. Our system – called Cyclops – dynamically adjusts the off-cloud bandwidth consumed by content servers (which represents the bulk of the provider's cost) to feed a set of swarming clients, based on a feedback signal that gauges the real-time health of the swarm. Our extensive evaluation of Cyclops in a variety of settings – including controlled PlanetLab and live Internet experiments involving thousands of users – show significant reduction in content distribution costs (by as much as two orders of magnitude) when compared to non-feedback-based swarming solutions, with minor impact on content delivery times

On the Impact of Seed Scheduling in Peer-to-Peer Networks

In a content distribution (file sharing) scenario, the initial phase is delicate due to the lack of global knowledge and the dynamics of the overlay. An unwise piece dissemination in this phase can cause delays in reaching steady state, thus increasing file download times. After showing that finding the scheduling strategy for optimal dissemination is computationally hard, even when the offline knowledge of the overlay is given, we devise a new class of scheduling algorithms at the seed (source peer with full content), based on a proportional fair approach, and we implement them on a real file sharing client. In addition to simulation results, we validated on our own file sharing client (BUTorrent) that our solution improves up to 25% the average downloading time of a standard file sharing protocol. Moreover, we give theoretical upper bounds on the improvements that our scheduling strategies may achieve