Self-organizing algorithms for cache cooperation in content distribution networks

Abstract

Introduction: The on-demand delivery of video content is anticipated to show tremendous growth over the next few years, driven by the huge popularity of user-generated video clips and the expansion of VoD libraries. Even stronger growth is likely to be fueled by the proliferation of IPTV services with personalized features such as CatchUp/PauseLive TV and NPVR capabilities. The common characteristic of these ‘time-shifted’ TV services, as well as VoD libraries and sites like YouTube, is that users can select from a vast collection of content material at any time they want. This runs counter to the broadcast paradigm embraced in conventional TV networks, and raises a need for unicast sessions, increasing the overall bandwidth demands by orders of magnitude. Caching strategies provide an effective mechanism for mitigating the massive bandwidth requirements associated with large-scale distribution of personalized high-definition video content. In essence, caching strategies exploit storage capacity to absorb traffic by replicating the most popular content closer to the network edge rather than storing it in a central location. The reduction in the traffic load translates into a smaller required transport capacity and capital expense as well as fewer performance bottlenecks, thus enabling better service quality at a lower price. In the present paper we develop light-weight distributed cooperative content placement algorithms so as to maximize the traffic volume served from cache, and thus minimize the bandwidth cost. As a canonical scenario, we focus on a cluster of distributed caches, connected either directly, or via a parent node, and formulate the content placement problem as an integer linear program in order to obtain a benchmark of the globally optimal performance. Under certain symmetry assumptions, the optimal solution of the relaxed linear program is found to have a rather simple structure. Besides interesting in its own right, the knowledge of the optimal structure offers useful insight for the design of low-complexity cooperative content placement and eviction algorithms. The performance of the proposed distributed algorithms is proved to be within a small constant factor from the performance of an optimal centralized scheme, while requiring only limited knowledge of global popularities, even in asymmetric scenarios. In contrast to [1, 2], we will focus on specific topologies, motivated by real system deployments, and use the insight from the linear program and the simple structure of its optimal solution to develop efficient distributed content placement algorithms with far more favorable performance ratios than the ones in [1, 2].