Minimizing Retrieval Cost of Multi-Layer Content Distribution Systems

Content distribution systems, such as on-demand video services [6], file-sharing networks [8,1], and content clouds [2], provide ubiquitous data access and data sharing for large numbers of end-users. To efficiently provide content access across geographic locations, content storage nodes with limited capacity are conventionally organized in a multi-layer architecture to facilitate vertical as well as horizontal peer content retrievals, each of which may have different bandwidth constraints and transport costs. Content management, i.e., caching strategies, is deployed to efficiently utilize storage nodes and further reduce network retrieval traffic and cost. An optimal system design of such a multi-layer system needs to accommodate the trade-offs between vertical communication, peer communication, storage capacity and the users' retrieval traffic, driven by caching policies. In this paper, we propose a generic optimization framework based on steady-state content diffusion to minimize the total content retrieval cost in multi-layer content distribution systems, while considering the aforementioned trade-offs. The derived optimal content diffusion can evaluate the optimality of caching policies, and dimension the size of the system and the node caching capacity. Furthermore, we develop Peer Aware Content Caching (PACC) policies based on the derived optimal content diffusion. Our simulation results show that PACC effectively caches content and minimizes vertical and horizontal content retrieval costs under different system scenarios.