Abstract-We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties which the current TCP implementation has at large windows. We describe the architecture and summarize some of the algorithms implemented in our prototype. We characterize its equilibrium and stability properties. We evaluate it experimentally in terms of throughput, fairness, stability, and responsiveness.

Abstract-Destination-based forwarding in traditional IP routers has not been able to take full advantage of multiple paths that frequently exist in Internet Service Provider Networks. As a result, the networks may not operate efficiently, especially when the traffic patterns are dynamic. This paper describes a multipath adaptive traffic engineering mechanism, called MATE, which is targeted for switched networks such as MultiProtocol Label Switching (MPLS) networks. The main goal of MATE is to avoid network congestion by adaptively balancing the load among multiple paths based on measurement and analysis of path congestion. MATE adopts a minimalist approach in that intermediate nodes are not required to perform traffic engineering or measurements besides normal packet forwarding. Moreover, MATE does not impose any particular scheduling, buffer management, or a priori traffic characterization on the nodes. This paper presents an analytical model, derives a class of MATE algorithms, and proves their convergence. Several practical design techniques to implement MATE are described. Simulation results are provided to illustrate the efficacy of MATE under various network scenarios.

No abstract

Abstract-Web content providers and content distribution network (CDN) operators often set up mirrors of popular content to improve performance. Due to the scale and decentralized administration of the Internet, companies have a limited number of sites (relative to the size of the Internet) where they can place mirrors. We formalize the mirror placement problem as a case of constrained mirror placement, where mirrors can only be placed on a preselected set of candidates. We study performance improvement in terms of client round-trip time (RTT) and server load when clients are clustered by the autonomous systems (AS) in which they reside. Our results show that, regardless of the mirror placement algorithm used, for only a surprisingly small range of values is increasing the number of mirror sites (under the constraint) effective in reducing client to server RTT and server load. In this range, we show that greedy placement performs the best.Index Terms-Constrained mirror placement, Internet experiments, performance analysis, placement algorithms.

HCF is easy to deploy, as it does not require any support from the underlying network. Through analysis using network measurement data, we show that HCF can identify close to 90% of spoofed IP packets, and then discard them with little collateral damage. We implement and evaluate HCF in the Linux kernel, demonstrating its effectiveness with experimental measurements.

Abstract-Web content providers and content distribution network (CDN) operators often set up mirrors of popular content to improve performance. Due to the scale and decentralized administration of the Internet, companies have a limited number of sites (relative to the size of the Internet) where they can place mirrors. We formalize the mirror placement problem as a case of constrained mirror placement, where mirrors can only be placed on a preselected set of candidates. We study performance improvement in terms of client round-trip time (RTT) and server load when clients are clustered by the autonomous systems (AS) in which they reside. Our results show that, regardless of the mirror placement algorithm used, for only a surprisingly small range of values is increasing the number of mirror sites (under the constraint) effective in reducing client to server RTT and server load. In this range, we show that greedy placement performs the best.Index Terms-Constrained mirror placement, Internet experiments, performance analysis, placement algorithms.

No abstract

Abstract. As tools for personal storage, file synchronization and data sharing, cloud storage services such as Dropbox have quickly gained popularity. These services provide users with ubiquitous, reliable data storage that can be automatically synced across multiple devices, and also shared among a group of users. To minimize the network overhead, cloud storage services employ binary diff, data compression, and other mechanisms when transferring updates among users. However, despite these optimizations, we observe that in the presence of frequent, short updates to user data, the network traffic generated by cloud storage services often exhibits pathological inefficiencies. Through comprehensive measurements and detailed analysis, we demonstrate that many cloud storage applications generate session maintenance traffic that far exceeds the useful update traffic. We refer to this behavior as the traffic overuse problem. To address this problem, we propose the update-batched delayed synchronization (UDS) mechanism. Acting as a middleware between the user's file storage system and a cloud storage application, UDS batches updates from clients to significantly reduce the overhead caused by session maintenance traffic, while preserving the rapid file synchronization that users expect from cloud storage services. Furthermore, we extend UDS with a backwards compatible Linux kernel modification that further improves the performance of cloud storage applications by reducing the CPU usage.