Algorithms for Constructing Overlay Networks For Live Streaming

We present a polynomial time approximation algorithm for constructing an overlay multicast network for streaming live media events over the Internet. The class of overlay networks constructed by our algorithm include networks used by Akamai Technologies to deliver live media events to a global audience with high fidelity. We construct networks consisting of three stages of nodes. The nodes in the first stage are the entry points that act as sources for the live streams. Each source forwards each of its streams to one or more nodes in the second stage that are called reflectors. A reflector can split an incoming stream into multiple identical outgoing streams, which are then sent on to nodes in the third and final stage that act as sinks and are located in edge networks near end-users. As the packets in a stream travel from one stage to the next, some of them may be lost. A sink combines the packets from multiple instances of the same stream (by reordering packets and discarding duplicates) to form a single instance of the stream with minimal loss. Our primary contribution is an algorithm that constructs an overlay network that provably satisfies capacity and reliability constraints to within a constant factor of optimal, and minimizes cost to within a logarithmic factor of optimal. Further in the common case where only the transmission costs are minimized, we show that our algorithm produces a solution that has cost within a factor of 2 of optimal. We also implement our algorithm and evaluate it on realistic traces derived from Akamai's live streaming network. Our empirical results show that our algorithm can be used to efficiently construct large-scale overlay networks in practice with near-optimal cost

Algorithms for optimizing bandwidth costs on the internet

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 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 (CIRs) and contracts that charge on a 95th –percentile basis