Security analysis of the micro transport protocol with a misbehaving receiver

BitTorrent is the most widely used Peer-to-Peer (P2P) protocol and it comprises the largest share of traffic in Europe. To make BitTorrent more Internet Service Provider (ISP) friendly, BitTorrent Inc. invented the Micro Transport Protocol (uTP). It is based on UDP with a novel congestion control called Low Extra Delay Background Transport (LEDBAT). This protocol assumes that the receiver always gives correct feedback, since otherwise this deteriorates throughput or yields to corrupted data. We show through experimental investigation that a misbehaving uTP receiver, which is not interested in data integrity, can increase the bandwidth of the sender by up to five times. This can cause a congestion collapse and steal large share of a victim’s bandwidth. We present three attacks, which increase the bandwidth usage significantly. We have tested these attacks in a real world environment and show its severity both in terms of number of packets and total traffic generated. We also present a countermeasure for protecting against the attacks and evaluate the performance of that defence strategy

Less-than-Best-Effort capacity sharing over high BDP networks with LEDBAT

There has been a renewed interest at the Internet Engineering Task Force (IETF) in using Less-than-Best Effort (LBE) methods for background applications. IETF recently published a RFC for Low Extra Delay Background Transport (LEDBAT), a congestion control algorithm for LBE transmissions. This paper provides an analysis of LEDBAT performance over congested large bandwidth X delay product (LBDP) networks, and assesses the validity of having a fixed target queuing time. In particular, we lead a study of the impact of this target queuing delay when LEDBAT is used over 4G satellite networks. The rationale is to explore the possibility to grab the unused 4G satellite links' capacity to carry non-commercial traffic. We show that this is achievable with LEDBAT. However, depending on the fluctuation of the load, performance improvements could be obtained by properly setting the target value. We generalize this evaluation over different congested LBDP networks and confirm that the target value might need to be adjusted to networks' and traffic's characteristics. Further work will study whether and how this parameter should be dynamically adapted, and LEDBAT's congestion control improved

Evaluation and optimisation of Less-than-Best-Effort TCP congestion control mechanisms

Increasing use of online software installation, updates, and backup services, as well as the popularity of user-generated content, has increased the demand for band-width in recent years. Traffic generated by these applications — when receiving a ‘fair-share’ of the available bandwidth — can impact the responsiveness of delay-sensitive applications. Less-than-Best-Effort TCP congestion control mechanisms aim to allow lower-priority applications to utilise excess bandwidth with minimum impact to regular TCP carrying delay-sensitive traffic. However, no previous study has evaluated the performance of a large number of this class of congestion con-trol mechanisms. This thesis quantifies the performance of existing Less-than-Best-Effort TCP congestion control mechanisms, and proposes a new mechanism to im-prove the performance of these mechanisms with high path delay. This study first evaluated the performance of seven Less-than-Best-Effort conges-tion control mechanisms in realistic scenarios under a range of network conditions in a Linux testbed incorporating wired Ethernet and 802.11n wireless links. The seven mechanisms evaluated were: Apple LEDBAT, CAIA Delay-Gradient (CDG), RFC6817 LEDBAT, Low Priority, Nice, Westwood-LP, and Vegas. Of these mecha-nisms, only four had existing implementations for modern operating systems. The remaining three mechanisms — Apple LEDBAT, Nice, and Westwood-LP — were implemented based on published descriptions and available code fragments to fa-cilitate this evaluation. The results of the evaluation suggest that Less-than-Best-Effort congestion control mechanisms can be divided into two categories: regular TCP-like mechanisms, and low-impact mechanisms. Of the low-impact mechanisms, two mechanisms were identified as having desirable performance characteristics: Nice and CDG. Nice pro-vides background throughput comparable to regular TCP while maintaining low queuing delay in low path delay settings. CDG has the least impact on regular TCP traffic, at the expense of reduced throughput. In high path-delay settings, these reductions to throughput experienced by CDG are exacerbated, while Nice has a greater impact on regular TCP traffic. To address the very low throughput of existing Less-than-Best-Effort congestion control mechanisms in high path-delay settings, a new Less-than-Best-Effort TCP congestion control algorithm was developed and implemented: Yield TCP. Yield utilises elements of a Proportional-Integral controller to better interpret and re-spond to changes in queuing delay to achieve this goal while also reducing the impact on regular TCP traffic over TCP-like mechanisms. Source code for the im-plementation of Yield developed for this research has also been made available. The results of evaluating Yield indicate that it successfully addresses the low through-put of low-impact Less-than-Best-Effort mechanisms in high delay settings, while also reducing the impact on foreground traffic compared to regular TCP-like con-gestion control mechanisms. Yield also performs similarly to Nice in low delay settings, while also achieving greater intra-protocol fairness than Nice across all settings. These results indicate that Yield addresses the weaknesses of Nice and CDG, and is a promising alternative to existing Less-than-Best-Effort congestion control algorithms

An experimental evaluation of LEDBAT++

LEDBAT++ is the evolution of LEDBAT, a congestion control algorithm originally designed to provide lessthan- best-effort transport on the Internet. LEDBAT++ aims to address a number of shortcomings present in LEDBAT, including late-comer advantage, latency drift, competition on equal grounds with best effort traffic in the presence of small buffers and difficulties experienced while measuring the variations on the delay. In this paper, we perform an experimental evaluation of LEDBAT++ using the Windows Server’s LEDBAT++ implementation. We find that while LEDBAT++ overcomes all the limitations identified in LEDBAT, the change introduced in LEDBAT++ to do so results in a performance penalty that prevents LEDBAT++ flows to seize all the available capacity when there is no competing traffic. We propose two simple modifications to the LEDBAT++ algorithm that would address the identified issues and reduce the penalty.This work has been partially supported by the EU EC through the NGI Pointer RIM project, Grant 871528 , and the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M21), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation)

Stochastic Forecasts Achieve High Throughput and Low Delay over Cellular Networks

Sprout is an end-to-end transport protocol for interactive applications that desire high throughput and low delay. Sprout works well over cellular wireless networks, where link speeds change dramatically with time, and current protocols build up multi-second queues in network gateways. Sprout does not use TCP-style reactive congestion control; instead the receiver observes the packet arrival times to infer the uncertain dynamics of the network path. This inference is used to forecast how many bytes may be sent by the sender, while bounding the risk that packets will be delayed inside the network for too long. In evaluations on traces from four commercial LTE and 3G networks, Sprout, compared with Skype, reduced self-inflicted end-to-end delay by a factor of 7.9 and achieved 2.2 the transmitted bit rate on average. Compared with Google’s Hangout, Sprout reduced delay by a factor of 7.2 while achieving 4.4 the bit rate, and compared with Apple’s Facetime, Sprout reduced delay by a factor of 8.7 with 1.9 the bit rate. Although it is end-to-end, Sprout matched or outperformed TCP Cubic running over the CoDel active queue management algorithm, which requires changes to cellular carrier equipment to deploy. We also tested Sprout as a tunnel to carry competing interactive and bulk traffic (Skype and TCP Cubic), and found that Sprout was able to isolate client application flows from one another.National Science Foundation (U.S.) (NSF Grant 1040072

Experimental Assessment of BitTorrent Completion Time in Heterogeneous TCP/uTP swarms

BitTorrent, one of the most widespread used P2P application for file-sharing, recently got rid of TCP by introducing an application-level congestion control protocol named uTP. The aim of this new protocol is to efficiently use the available link capacity, while minimizing its interference with the rest of user traffic (e.g., Web, VoIP and gaming) sharing the same access bottleneck. In this paper we perform an experimental study of the impact of uTP on the torrent completion time, the metric that better captures the user experience. We run BitTorrent applications in a flash crowd scenario over a dedicated cluster platform, under both homogeneous and heterogeneous swarm population. Experiments show that an all-uTP swarms have shorter torrent download time with respect to all-TCP swarms. Interestingly, at the same time, we observe that even shorter completion times can be achieved under careful mixtures of TCP and uTP traffic.Comment: 14 pages, under submissio

Transport Architectures for an Evolving Internet

In the Internet architecture, transport protocols are the glue between an application’s needs and the network’s abilities. But as the Internet has evolved over the last 30 years, the implicit assumptions of these protocols have held less and less well. This can cause poor performance on newer networks—cellular networks, datacenters—and makes it challenging to roll out networking technologies that break markedly with the past. Working with collaborators at MIT, I have built two systems that explore an objective-driven, computer-generated approach to protocol design. My thesis is that making protocols a function of stated assumptions and objectives can improve application performance and free network technologies to evolve. Sprout, a transport protocol designed for videoconferencing over cellular networks, uses probabilistic inference to forecast network congestion in advance. On commercial cellular networks, Sprout gives 2-to-4 times the throughput and 7-to-9 times less delay than Skype, Apple Facetime, and Google Hangouts. This work led to Remy, a tool that programmatically generates protocols for an uncertain multi-agent network. Remy’s computer-generated algorithms can achieve higher performance and greater fairness than some sophisticated human-designed schemes, including ones that put intelligence inside the network. The Remy tool can then be used to probe the difficulty of the congestion control problem itself—how easy is it to “learn” a network protocol to achieve desired goals, given a necessarily imperfect model of the networks where it ultimately will be deployed? We found weak evidence of a tradeoff between the breadth of the operating range of a computer-generated protocol and its performance, but also that a single computer-generated protocol was able to outperform existing schemes over a thousand-fold range of link rates

A delay-based aggregate rate control for P2P streaming systems

In this paper we consider mesh based P2P streaming systems focusing on the problem of regulating peer transmission rate to match the system demand while not overloading each peer upload link capacity. We propose Hose Rate Control (HRC), a novel scheme to control the speed at which peers offer chunks to other peers, ultimately controlling peer uplink capacity utilization. This is of critical importance for heterogeneous scenarios like the one faced in the Internet, where peer upload capacity is unknown and varies widely. HRC nicely adapts to the actual peer available upload bandwidth and system demand, so that Quality of Experience is greatly enhanced. To support our claims we present both simulations and actual experiments involving more than 1000 peers to assess performance in real scenarios. Results show that HRC consistently outperforms the Quality of Experience achieved by non-adaptive scheme