Performance Analysis of Server Sharing Collectives for Content Distribution

Abstract

Demand for content served by a provider can fluctuate with time, complicating the task of provisioning serving resources so that requests for its content are not rejected. One way to address this problem is to have providers form a collective in which they pool together their serving resources to assist in servicing requests for one another’s content. In this paper, we determine the conditions under which a provider’s participation in a collective reduces the rejection rate of requests for its content - a property that is necessary for the provider to justify participating in the collective. We show that all request rejection rates are reduced when the collective is formed from a homogeneous set of providers, but that some rates can increase within heterogeneous sets of collectives. We also show that asymptotically, growing the size of the collective will sometimes, but not always resolve this problem. We explore the use of thresholding techniques, where each collective participant sets aside a portion of its serving resources to serve only requests for its own content. We show that thresholding allows a more diverse set of providers to benefit from the collective model, making collectives a more viable option for content delivery services.

This material was supported in part by the National Science Foundation under Grant No. ANI-0117738 and CAREER Award No. 0133829. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Daniel Villela received scholarship support from CNPq-Brazil (Ref. No. 200168/98-3).