Abstract-By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of selfinterested users that would benefit from colocation on shared instances. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. CaaS could be incorporated into an IaaS offering by providers; it could be implemented as a valueadded proposition by IaaS resellers; or it could be directly leveraged in a peer-to-peer fashion by IaaS users. To establish the practicality of such offerings, this paper presents XCS -a prototype implementation of CaaS on top of the Xen hypervisor. XCS makes specific choices with respect to the various elements of the CaaS framework: it implements strategic services based on a game-theoretic formulation of colocation; it features novel concurrent migration heuristics which are shown to be efficient; and it offers monitoring and accounting services at both the hypervisor and VM layers. Extensive experimental results obtained by running PlanetLab trace-driven workloads on the XCS prototype confirm the premise of CaaS -by demonstrating the efficiency and scalability of XCS, and by quantifying the potential cost savings accrued through the use of XCS.

Abstract-Leveraging client upload capacity through peerassisted 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 peerassisted 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.

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Increasingly, commercial content providers (CPs) offer streaming and IPTV solutions that leverage an underlying peerto-peer (P2P) stream distribution architecture. The use of P2P protocols promises significant scalability and cost savings by leveraging the local resources of clients-specifically, uplink capacity. A major limitation of P2P live streaming is that playout rates are constrained by the uplink capacities of clients, which are typically much lower than downlink capacities, thus limiting the quality of the delivered stream.

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