FAST TCP: Motivation, Architecture, Algorithms, Performance

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

Delay-oriented active queue management in TCP/IP networks

PhDInternet-based applications and services are pervading everyday life. Moreover, the growing popularity of real-time, time-critical and mission-critical applications set new challenges to the Internet community. The requirement for reducing response time, and therefore latency control is increasingly emphasized. This thesis seeks to reduce queueing delay through active queue management. While mathematical studies and research simulations reveal that complex trade-off relationships exist among performance indices such as throughput, packet loss ratio and delay, etc., this thesis intends to find an improved active queue management algorithm which emphasizes delay control without trading much on other performance indices such as throughput and packet loss ratio. The thesis observes that in TCP/IP network, packet loss ratio is a major reflection of congestion severity or load. With a properly functioning active queue management algorithm, traffic load will in general push the feedback system to an equilibrium point in terms of packet loss ratio and throughput. On the other hand, queue length is a determinant factor on system delay performance while has only a slight influence on the equilibrium. This observation suggests the possibility of reducing delay while maintaining throughput and packet loss ratio relatively unchanged. The thesis also observes that queue length fluctuation is a reflection of both load changes and natural fluctuation in arriving bit rate. Monitoring queue length fluctuation alone cannot distinguish the difference and identify congestion status; and yet identifying this difference is crucial in finding out situations where average queue size and hence queueing delay can be properly controlled and reasonably reduced. However, many existing active queue management algorithms only monitor queue length, and their control policies are solely based on this measurement. In our studies, our novel finding is that the arriving bit rate distribution of all sources contains information which can be a better indication of congestion status and has a correlation with traffic burstiness. And this thesis develops a simple and scalable way to measure its two most important characteristics, namely the mean ii and the variance of the arriving rate distribution. The measuring mechanism is based on a Zombie List mechanism originally proposed and deployed in Stabilized RED to estimate the number of flows and identify misbehaving flows. This thesis modifies the original zombie list measuring mechanism, makes it capable of measuring additional variables. Based on these additional measurements, this thesis proposes a novel modification to the RED algorithm. It utilizes a robust adaptive mechanism to ensure that the system reaches proper equilibrium operating points in terms of packet loss ratio and queueing delay under various loads. Furthermore, it identifies different congestion status where traffic is less bursty and adapts RED parameters in order to reduce average queue size and hence queueing delay accordingly. Using ns-2 simulation platform, this thesis runs simulations of a single bottleneck link scenario which represents an important and popular application scenario such as home access network or SoHo. Simulation results indicate that there are complex trade-off relationships among throughput, packet loss ratio and delay; and in these relationships delay can be substantially reduced whereas trade-offs on throughput and packet loss ratio are negligible. Simulation results show that our proposed active queue management algorithm can identify circumstances where traffic is less bursty and actively reduce queueing delay with hardly noticeable sacrifice on throughput and packet loss ratio performances. In conclusion, our novel approach enables the application of adaptive techniques to more RED parameters including those affecting queue occupancy and hence queueing delay. The new modification to RED algorithm is a scalable approach and does not introduce additional protocol overhead. In general it brings the benefit of substantially reduced delay at the cost of limited processing overhead and negligible degradation in throughput and packet loss ratio. However, our new algorithm is only tested on responsive flows and a single bottleneck scenario. Its effectiveness on a combination of responsive and non-responsive flows as well as in more complicated network topology scenarios is left for future work

Router-based algorithms for improving internet quality of service.

We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows. We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations. We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them. In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links. While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it

Router-based algorithms for improving internet quality of service.

We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows. We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations. We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them. In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links. While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it

Downstream Bandwidth Management for Emerging DOCSIS-based Networks

In this dissertation, we consider the downstream bandwidth management in the context of emerging DOCSIS-based cable networks. The latest DOCSIS 3.1 standard for cable access networks represents a significant change to cable networks. For downstream, the current 6 MHz channel size is replaced by a much larger 192 MHz channel which potentially can provide data rates up to 10 Gbps. Further, the current standard requires equipment to support a relatively new form of active queue management (AQM) referred to as delay-based AQM. Given that more than 50 million households (and climbing) use cable for Internet access, a clear understanding of the impacts of bandwidth management strategies used in these emerging networks is crucial. Further, given the scope of the change provided by emerging cable systems, now is the time to develop and introduce innovative new methods for managing bandwidth. With this motivation, we address research questions pertaining to next generation of cable access networks. The cable industry has had to deal with the problem of a small number of subscribers who utilize the majority of network resources. This problem will grow as access rates increase to gigabits per second. Fundamentally this is a problem on how to manage data flows in a fair manner and provide protection. A well known performance issue in the Internet, referred to as bufferbloat, has received significant attention recently. High throughput network flows need sufficiently large buffer to keep the pipe full and absorb occasional burstiness. Standard practice however has led to equipment offering very large unmanaged buffers that can result in sustained queue levels increasing packet latency. One reason why these problems continue to plague cable access networks is the desire for low complexity and easily explainable (to access network subscribers and to the Federal Communications Commission) bandwidth management. This research begins by evaluating modern delay-based AQM algorithms in downstream DOCSIS 3.0 environments with a focus on fairness and application performance capabilities of single queue AQMs. We are especially interested in delay-based AQM schemes that have been proposed to combat the bufferbloat problem. Our evaluation involves a variety of scenarios that include tiered services and application workloads. Based on our results, we show that in scenarios involving realistic workloads, modern delay-based AQMs can effectively mitigate bufferbloat. However they do not address the other problem related to managing the fairness. To address the combined problem of fairness and bufferbloat, we propose a novel approach to bandwidth management that provides a compromise among the conflicting requirements. We introduce a flow quantization method referred to as adaptive bandwidth binning where flows that are observed to consume similar levels of bandwidth are grouped together with the system managed through a hierarchical scheduler designed to approximate weighted fairness while addressing bufferbloat. Based on a simulation study that considers many system experimental parameters including workloads and network configurations, we provide evidence of the efficacy of the idea. Our results suggest that the scheme is able to provide long term fairness and low delay with a performance close to that of a reference approach based on fair queueing. A further contribution is our idea for replacing `tiered\u27 levels of service based on service rates with tiering based on weights. The application of our bandwidth binning scheme offers a timely and innovative alternative to broadband service that leverages the potential offered by emerging DOCSIS-based cable systems

Application of learning algorithms to traffic management in integrated services networks.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Explicit congestion control algorithms for available bit rate services in asynchronous transfer mode networks

Congestion control of available bit rate (ABR) services in asynchronous transfer mode (ATM) networks has been the recent focus of the ATM Forum. The focus of this dissertation is to study the impact of queueing disciplines on ABR service congestion control, and to develop an explicit rate control algorithm. Two queueing disciplines, namely, First-In-First-Out (FIFO) and per-VC (virtual connection) queueing, are examined. Performance in terms of fairness, throughput, cell loss rate, buffer size and network utilization are benchmarked via extensive simulations. Implementation complexity analysis and trade-offs associated with each queueing implementation are addressed. Contrary to the common belief, our investigation demonstrates that per-VC queueing, which is costlier and more complex, does not necessarily provide any significant improvement over simple FIFO queueing. A new ATM switch algorithm is proposed to complement the ABR congestion control standard. The algorithm is designed to work with the rate-based congestion control framework recently recommended by the ATM Forum for ABR services. The algorithm\u27s primary merits are fast convergence, high throughput, high link utilization, and small buffer requirements. Mathematical analysis is done to show that the algorithm converges to the max-min fair allocation rates in finite time, and the convergence time is proportional to the distinct number of fair allocations and the round-trip delays in the network. At the steady state, the algorithm operates without causing any oscillations in rates. The algorithm does not require any parameter tuning, and proves to be very robust in a large ATM network. The impact of ATM switching and ATM layer congestion control on the performance of TCP/IP traffic is studied and the results are presented. The study shows that ATM layer congestion control improves the performance of TCP/IP traffic over ATM, and implementing the proposed switch algorithm drastically reduces the required switch buffer requirements. In order to validate claims, many benchmark ATM networks are simulated, and the performance of the switch is evaluated in terms of fairness, link utilization, response time, and buffer size requirements. In terms of performance and complexity, the algorithm proposed here offers many advantages over other proposed algorithms in the literature

A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning

In this tutorial paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalent rate constraint approach, the Lyapunov stability drift approach and the approximate Markov Decision Process (MDP) approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the approaches, the problem setup, the general solution and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multi-hop routing designs in general multi-hop networks are elaborated. Finally, the delay performance of the various approaches are compared through simulations using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201