Using Tuangou to reduce IP transit costs

A majority of ISPs (Internet Service Providers) support connectivity to the entire Internet by transiting their traffic via other providers. Although the transit prices per Mbps decline steadily, the overall transit costs of these ISPs remain high or even increase, due to the traffic growth. The discontent of the ISPs with the high transit costs has yielded notable innovations such as peering, content distribution networks, multicast, and peer-to-peer localization. While the above solutions tackle the problem by reducing the transit traffic, this paper explores a novel approach that reduces the transit costs without altering the traffic. In the proposed CIPT (Cooperative IP Transit), multiple ISPs cooperate to jointly purchase IP (Internet Protocol) transit in bulk. The aggregate transit costs decrease due to the economies-of-scale effect of typical subadditive pricing as well as burstable billing: not all ISPs transit their peak traffic during the same period. To distribute the aggregate savings among the CIPT partners, we propose Shapley-value sharing of the CIPT transit costs. Using public data about IP traffic of 264 ISPs and transit prices, we quantitatively evaluate CIPT and show that significant savings can be achieved, both in relative and absolute terms. We also discuss the organizational embodiment, relationship with transit providers, traffic confidentiality, and other aspects of CIPT

A Network Architecture for Large-Scale Science

Needs of large-scale science have driven the field of high-performance computing and yielded impressive designs that differ vastly from ubiquitous personal computers in terms of both performance and architecture. In a vision behind this paper, computer networks for large-scale science should also be architecturally different from the ubiquitous Internet, partly in order to sustain high performance needed by distributed scientific applications. While the layered Internet architecture is designed for horizontal scalability (i.e., the ability to interconnect arbitrary numbers of devices from various administrative domains with no restrictions on communication media), the Internet failure to optimize for performance is a fundamental and growing problem for large-scale science. For example, while modern optical media promise communications at Tbps rates that scientific applications clamor for, the inability of Transmission Control Protocol (TCP) to utilize effectively the available communication capacity becomes painfully obvious. We argue for a high-performance networking architecture that explicitly accounts for and reconciles application needs and communication capabilities. Such awareness is certainly attractive in general network settings as well. However, focusing on the specialized domain of large-scale science makes providing this functionality feasible. First, we envision the architecture for networks with a relatively small number of nodes. Our primary objective is to support high-performance computing across few sites distributed over a wide geographical area. Second, there is no attempt to incorporate arbitrary communication media. In particular, we do not target wireless communication between mobile devices, which is less amenable to large-scal