Design and analysis of a scalable terabit multicast packet switch : architecture and scheduling algorithms

Internet growth and success not only open a primary route of information exchange for millions of people around the world, but also create unprecedented demand for core network capacity. Existing switches/routers, due to the bottleneck from either switch architecture or arbitration complexity, can reach a capacity on the order of gigabits per second, but few of them are scalable to large capacity of terabits per second. In this dissertation, we propose three novel switch architectures with cooperated scheduling algorithms to design a terabit backbone switch/router which is able to deliver large capacity, multicasting, and high performance along with Quality of Service (QoS). Our switch designs benefit from unique features of modular switch architecture and distributed resource allocation scheme. Switch I is a unique and modular design characterized by input and output link sharing. Link sharing resolves output contention and eliminates speedup requirement for central switch fabric. Hence, the switch architecture is scalable to any large size. We propose a distributed round robin (RR) scheduling algorithm which provides fairness and has very low arbitration complexity. Switch I can achieve good performance under uniform traffic. However, Switch I does not perform well for non-uniform traffic. Switch II, as a modified switch design, employs link sharing as well as a token ring to pursue a solution to overcome the drawback of Switch 1. We propose a round robin prioritized link reservation (RR+POLR) algorithm which results in an improved performance especially under non-uniform traffic. However, RR+POLR algorithm is not flexible enough to adapt to the input traffic. In Switch II, the link reservation rate has a great impact on switch performance. Finally, Switch III is proposed as an enhanced switch design using link sharing and dual round robin rings. Packet forwarding is based on link reservation. We propose a queue occupancy based dynamic link reservation (QOBDLR) algorithm which can adapt to the input traffic to provide a fast and fair link resource allocation. QOBDLR algorithm is a distributed resource allocation scheme in the sense that dynamic link reservation is carried out according to local available information. Arbitration complexity is very low. Compared to the output queued (OQ) switch which is known to offer the best performance under any traffic pattern, Switch III not only achieves performance as good as the OQ switch, but also overcomes speedup problem which seriously limits the OQ switch to be a scalable switch design. Hence, Switch III would be a good choice for high performance, scalable, large-capacity core switches

Some aspects of traffic control and performance evaluation of ATM networks

The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation

Long-range dependence and performance in telecom networks

SUMMARY Telecommunications systems have recently undergone significant innovations. These call for suitable statistical models that can properly describe the behaviour of the input traffic in a network. Here we use fractional Brownian motion (FBM) to model cumulative traffic network, thus taking into account the possible presence of long-range dependence in the data. A Bayesian approach is devised in such a way that we are able to: (a) estimate the Hurst parameter H of the FBM; (b) estimate the overflow probability which is a parameter measuring the quality of service of a network: (c) develop a test for comparing the null hypothesis of long-range dependence in the data versus the alternative of short-range dependence. In order to achieve these inferential results, we elaborate an MCMC sampling scheme whose output enables us to obtain an approximation of the quantities of interest. An application to three real datasets, corresponding to three different levels of traffic, is finally considered

Improving the Performance of Internet Data Transport

With the explosion of the World Wide Web, the Internet infrastructure faces new challenges in providing high performance for data traffic. First, it must be able to pro-vide a fair-share of congested link bandwidth to every flow. Second, since web traffic is inherently interactive, it must minimize the delay for data transfer. Recent studies have shown that queue management algorithms such as Tail Drop, RED and Blue are deficient in providing high throughput, low delay paths for a data flow. Two major shortcomings of the current algorithms are: they allow TCP flows to get synchronized and thus require large buffers during congestion to enable high throughput; and they allow unfair bandwidth usage for shorter round-trip time TCP flows. We propose algorithms using multiple queues and discard policies with hysteresis at bottleneck routers to address both these issues. Us-ing ns-2 simulations, we show that these algorithms can significantly outperform RED and Blue, especially at smaller buffer sizes. Using multiple queues raises two new concerns: scalability and excess memory bandwidth usage caused by dropping packets which have been queued. We propose and evaluate an architecture using Bloom filters to evenly distribute flows among queues to improve scalability. We have also developed new intelligent packet discard algorithms that discard packets on arrival and are able to achieve performance close to that of policies that may discard packets that have already been queued. Finally, we propose better methods for evaluating the performance of fair-queueing methods. In the current literature, fair-queueing methods are evaluated based on their worst-case performance. This can exaggerate the differences among algorithms, since the worst-case behavior is dependent on the the precise timing of packet arrivals. This work seeks to understand what happens under more typical circumstances

Statistical multiplexing and connection admission control in ATM networks

Asynchronous Transfer Mode (ATM) technology is widely employed for the transport of network traffic, and has the potential to be the base technology for the next generation of global communications. Connection Admission Control (CAC) is the effective traffic control mechanism which is necessary in ATM networks in order to avoid possible congestion at each network node and to achieve the Quality-of-Service (QoS) requested by each connection. CAC determines whether or not the network should accept a new connection. A new connection will only be accepted if the network has sufficient resources to meet its QoS requirements without affecting the QoS commitments already made by the network for existing connections. The design of a high-performance CAC is based on an in-depth understanding of the statistical characteristics of the traffic sources

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

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Delay Bound: Fractal Traffic Passes through Network Servers

Delay analysis plays a role in real-time systems in computer communication networks. This paper gives our results in the aspect of delay analysis of fractal traffic passing through servers. There are three contributions presented in this paper. First, we will explain the reasons why conventional theory of queuing systems ceases in the general sense when arrival traffic is fractal. Then, we will propose a concise method of delay computation for hard real-time systems as shown in this paper. Finally, the delay computation of fractal traffic passing through severs is presented

A review of connection admission control algorithms for ATM networks

The emergence of high-speed networks such as those with ATM integrates large numbers of services with a wide range of characteristics. Admission control is a prime instrument for controlling congestion in the network. As part of connection services to an ATM system, the Connection Admission Control (CAC) algorithm decides if another call or connection can be admitted to the Broadband Network. The main task of the CAC is to ensure that the broadband resources will not saturate or overflow within a very small probability. It limits the connections and guarantees Quality of Service for the new connection. The algorithm for connection admission is crucial in determining bandwidth utilisation efficiency. With statistical multiplexing more calls can be allocated on a network link, while still maintaining the Quality of Service specified by the connection with traffic parameters and type of service. A number of algorithms for admission control for Broadband Services with ATM Networks are described and compared for performance under different traffic loads. There is a general description of the ATM Network as an introduction. Issues to do with source distributions and traffic models are explored in Chapter 2. Chapter 3 provides an extensive presentation of the CAC algorithms for ATM Broadband Networks. The ideas about the Effective Bandwidth are reviewed in Chapter 4, and a different approach to admission control using online measurement is presented in Chapter 5. Chapter 6 has the numerical evaluation of four of the key algorithms, with simulations. Finally Chapter 7 has conclusions of the findings and explores some possibilities for further work

Simulation and analytical performance studies of generic atm switch fabrics.

As technology improves exciting new services such as video phone become possible and economically viable but their deployment is hampered by the inability of the present networks to carry them. The long term vision is to have a single network able to carry all present and future services. Asynchronous Transfer Mode, ATM, is the versatile new packet -based switching and multiplexing technique proposed for the single network. Interest in ATM is currently high as both industrial and academic institutions strive to understand more about the technique. Using both simulation and analysis, this research has investigated how the performance of ATM switches is affected by architectural variations in the switch fabric design and how the stochastic nature of ATM affects the timing of constant bit rate services. As a result the research has contributed new ATM switch performance data, a general purpose ATM switch simulator and analytic models that further research may utilise and has uncovered a significant timing problem of the ATM technique. The thesis will also be of interest and assistance to anyone planning on using simulation as a research tool to model an ATM switch