Abstract. Most congestion control algorithms try to emulate processor sharing (PS) by giving each competing flow an equal share of a bottleneck link. This approach leads to fairness, and prevents long flows from hogging resources. For example, if a set of flows with the same round trip time share a bottleneck link, TCP's congestion control mechanism tries to achieve PS; so do most of the proposed alternatives, such as eXplicit Control Protocol (XCP). But although they emulate PS well in a static scenario when all flows are long-lived, they do not come close to PS when new flows arrive randomly and have a finite amount of data to send, as is the case in today's Internet. Typically, flows take an order of magnitude longer to complete with TCP or XCP than with PS, suggesting large room for improvement. And so in this paper, we explore how a new congestion control algorithm -Rate Control Protocol (RCP) -comes much closer to emulating PS over a broad range of operating conditions. In RCP, a router assigns a single rate to all flows that pass through it. The router does not keep flow-state, and does no per-packet calculations. Yet we are able to show that under a wide range of traffic characteristics and network conditions, RCP's performance is very close to ideal processor sharing.

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Abstract. Network operators would like their network to support current and future traffic matrices, even when links and routers fail. Not surprisingly, no backbone network can do this today: It is hard to accurately measure the current matrix, and harder still to predict future ones. Even if the matrices are known, how do we know a network will support them, particularly under failures? As a result, today's networks are designed in a somewhat ad-hoc fashion, using rules-of-thumb and crude estimates of current and future traffic.Previously we proposed the use of Valiant Load-balancing (VLB) for backbone design. It can guarantee 100% throughput to any traffic matrix, even under link and router failures. Our initial work was limited to homogeneous backbones in which routers had the same capacity. In this paper we extend our results in two ways: First, we show that the same qualities of service (guaranteed support of any traffic matrix with or without failure) can be achieved in a realistic heterogeneous backbone network; and second, we show that VLB is optimal, in the sense that the capacity required by VLB is very close to the lower bound of total capacity needed by any architecture in order to support all traffic matrices.

Traditionally, Internet Service Providers (ISPs) make profit by providing Internet connectivity, while content providers (CPs) play the more lucrative role of delivering content to users. As network connectivity is increasingly a commodity, ISPs have a strong incentive to offer content to their subscribers by deploying their own content distribution infrastructure. Providing content services in a provider network presents new opportunities for coordination between server selection (to match servers with subscribers) and traffic engineering (to select efficient routes for the traffic). In this work, we utilize a mathematical framework to show that separating server selection and traffic engineering leads to a sub-optimal equilibrium, even when the CP is given accurate and timely information about network conditions. Leveraging ideas from cooperative game theory, we propose that the system implements a Nash bargaining solution that significantly improves the fairness and efficiency of the joint system. This study is another step toward a systematic understanding of the interactions between those who generate and distribute content and those who provide and operate networks.

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