Algorithms for optimizing the bandwidth cost of content delivery

Abstract

Content Delivery Networks (CDNs) deliver web content to end-users from a large distributed platform of web servers hosted in data centers belonging to thousands of Internet Service Providers (ISPs) around the world. The bandwidth cost incurred by a CDN is the sum of the amounts it pays each ISP for routing traffic from its servers located in that ISP out to end-users. A large enterprise may also contract with multiple ISPs to provide redundant Internet access for its origin infrastructure using technologies such as multihoming and mirroring, thereby incurring a significant bandwidth cost across multiple ISPs. This paper initiates the formal algorithmic study of bandwidth cost minimization in the context of a large enterprise or a CDN, a problem area that is both algorithmically rich and practically very important. First, we model different types of contracts that are used in practice by ISPs to charge for bandwidth usage, including average, maximum, and 95th-percentile contracts. Then, we devise an optimal offline algorithm that routes traffic to achieve the minimum bandwidth cost, when the network contracts charge either on a maximum or on an average basis. Next, we devise a deterministic (resp., randomized) online algorithm that achieves cost that is within a factor of 2 (resp., e e - 1 ) of the optimal offline cost for maximum and average contracts. In addition, we prove that our online algorithms achieve the best possible competitive ratios in both the deterministic and the randomized cases. An interesting theoretical contribution of this work is that we show intriguing connections between the online bandwidth optimization problem and the seemingly-unrelated but well-studied ski rental problem where similar optimal competitive ratios are known to hold. Finally, we consider extensions for contracts with a committed amount of spend (known as committed information rate or CIR) and contracts that charge on a 95th-percentile basis.