Scale and Performance in the CoBlitz Large-File Distribution Service
Scalable distribution of large files has been the area of much research and commercial interest in the past few years. In this paper, we describe the CoBlitz system, which efficiently distributes large files using a content distribution network (CDN) designed for HTTP. As a result, CoBlitz is able to serve large files without requiring any modifications to standard Web servers and clients, making it an interesting option both for end users as well as infrastructure services. Over the 18 months that CoBlitz and its partner service, CoDeploy, have been running on PlanetLab, we have had the opportunity to observe its algorithms in practice, and to evolve its design. These changes stem not only from observations on its use, but also from a better understanding of their behavior in real-world conditions. This utilitarian approach has led us to better understand the effects of scale, peering policies, replication behavior, and congestion, giving us new insights into how to better improve their performance. With these changes, CoBlitz is able to deliver in excess of 1 Gbps on PlanetLab, and to outperform a range of systems, including research systems as well as the widely-used BitTorrent.

title: Securing Web Service by Automatic Robot Detection
abstract: Web sites are routinely visited by automated agents known as Web robots, that perform acts ranging from the beneficial, such as indexing for search engines, to the malicious, such as searching for vulnerabilities, attempting to crack passwords, or spamming bulletin boards. Previous work to identify malicious robots has relied on ad-hoc signature matching and has been performed on a per-site basis. As Web robots evolve and diversify, these techniques have not been scaling. 
 
We approach the problem as a special form of the Turing test and defend the system by inferring if the traffic source is human or robot. By extracting the implicit patterns of human Web browsing, we develop simple yet effective algorithms to detect human users. Our experiments with the CoDeeN content distribution network show that 95% of human users are detected within the first 57 requests, and 80% can be identified in only 20 requests, with a maximum false positive rate of 2.4%. In the time that this system has been deployed on CoDeeN, robot-related abuse complaints have dropped by a factor of 10.

title: On the effectiveness of route-based packet filtering for distributed DoS attack prevention in power-law internets
abstract: Denial of service (DoS) attack on the Internet has become a pressing problem. In this paper, we describe and evaluate route-based distributed packet filtering (DPF), a novel approach to distributed DoS (DDoS) attack prevention. We show that DPF achieves proactiveness and scalability, and we show that there is an intimate relationship between the effectiveness of DPF at mitigating DDoS attack and power-law network topology.The salient features of this work are two-fold. First, we show that DPF is able to proactively filter out a significant fraction of spoofed packet flows and prevent attack packets from reaching their targets in the first place. The IP flows that cannot be proactively curtailed are extremely sparse so that their origin can be localized---i.e., IP traceback---to within a small, constant number of candidate sites. We show that the two proactive and reactive performance effects can be achieved by implementing route-based filtering on less than 20% of Internet autonomous system (AS) sites. Second, we show that the two complementary performance measures are dependent on the properties of the underlying AS graph. In particular, we show that the power-law structure of Internet AS topology leads to connectivity properties which are crucial in facilitating the observed performance effects.

title: A Linear-Time Algorithm for Concave One-Dimensional Dynamic Programming

title: Performance evaluation of multiple time scale TCP under self-similar traffic conditions
abstract: Measurements of network traffic have shown that self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting long-range correlation structure in self-similar traffic for congestion control. We have advanced the framework of multiple time scale congestion control and shown its effectiveness at enhancing performance for rate-based feedback control. In this article, we extend the multiple time scale control framework to window-based congestion control, in particular, TCP. This is performed by interfacing TCP with a large time scale module that adjusts the aggressiveness of bandwidth consumpton behavior exhibited by TCP as a function of large time scale network state, that is, information that exceeds the time horizon of the feedback loop as determined by RTT. How to effectively utilize such information—due to its probabilistic nature, dispersion over multiple time scales, and realization on top of existing window-based congestion controls—is a nontrivial problem. First, we define a modular extension of TCP (a function call with a simple interface that applies to various flavors of TCP, e.g., Tahoe, Reno, and Vegas) and show that it significantly improves performance. Second, we show that multiple time scale TCP endows the underlying feedback control with proacativity by bridging the uncertainty gap associated with reactive controls which is exacerbated by the high delay-bandwidth product in broadband wide area networks. Third, we investigate the influence of three traffic control dimensions—tracking ability, connection duration, and fairness—on performance. Performance evaluation of multiple time scale TCP is facilitated by a simulation benchmark environment based on physical modeling of self-similar traffic. We explicate our methodology for disc

title: On the relationship between file sizes, transport protocols, and self-similar network traffic
abstract: Measurements of LAN and WAN traffic show that network traffic exhibits variability on different scales. We examine a mechanism that gives rise to self-similar network traffic and discuss performance. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. In a realistic client/server network the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. This causal relationship is robust relative to changes in network resources, network topology, the influence of cross-traffic, and the distribution of interarrival times. Properties of the transport layer play an important role in preserving and modulating this relationship. The reliable transmission and flow control mechanisms of TCP serve to maintain the long-range dependency structure induced by heavy-tailed file size distributions. In contrast, if a non-flow-controlled and unreliable (UDP-based) transport protocol is used, the resulting traffic shows little self-similarity: although still bursty at short time scales, it has little long-range dependence. Performance implications of self-similarity are discussed as represented by various performance measures. Increased self-similarity as expected, results in degradation of performance. Queueing delay, in particular is discussed. Throughput-related measures such as packet loss and retransmission rate, however increase only gradually with increasing traffic self-similarity as long as reliable, flow-controlled transport protocol is used.

title: QoS-sensitive transport of real-time MPEG video using adaptive redundancy control
abstract: This paper presents an adaptive end-to-end protocol for quality of service (QoS)-sensitive transport of real-time MPEG video using packet-level forward error correction in dynamic networks. The objective is to facilitate a user-specified QoS end-to-end - i.e. without special network support - for real-time MPEG video whose timing constraints rule out the use of retransmission-based congestion control and QoS provisioning schemes. The degree of redundancy - overcode in forward error correction - injected into the network is adjusted as a function of network state, decreasing when the network is well-behaved to minimize unnecessary network resource consumption, and increasing when it is not to compensate for adverse network effects so as to maintain an invariant level of end-to-end QoS. We describe an adaptive packet-level forward error correction protocol called AFEC and analyze its properties with respect to optimality and stability. The optimal control problem is nontrivial due to the fact that increased redundancy, beyond a certain point, can backfire resulting in self-induced congestion which impedes the timely recovery of information - MPEG video frames - at the receiver. We experimentally evaluate the efficacy of our end-to-end QoS control by implementing and customizing AFEC to the transport of real-time MPEG video. We realize the system as a transport/application layer protocol running on UNIX workstations, and measure its performance over controlled network environments. We show that AFEC is able to effectively hide potentially adverse network effects such as packet drops and delays stemming from traffic burstiness and nonstationary structural changes using adaptive redundancy control, exporting a constant QoS service commensurate with user-specified QoS.