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

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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

Performance analysis of error recovery and congestion control in high-speed networks

In the past few years, Broadband Integrated Services Digital Network (B-ISDN) has received increasing attention as a communication architecture capable of supporting multimedia applications. Among the techniques proposed to implement B-ISDN, Asynchronous Transfer Mode (ATM) is considered to be the most promising transfer technique because of its efficiency and flexibility.In ATM networks, the performance bottleneck of the network, which was once the channel transmission speed, is shifted to the processing speed at the network switching nodes and the propagation delay of the channel. This shift is because the high-speed channel increases the ratio of processing time to packet transmission time and also the ratio of propagation delay to packet transmission time. The increased processing overhead makes it difficult to implement hop-by-hop schemes, which may impose prohibitably high processing at each switching node. The increased propagation delay overhead makes traffic control in ATM a challenge since a large number of packets can be in transit between two ATM switching nodes. Because of these fundamental changes, control schemes developed for traditional networks may not perform efficiently, and thus, new network architectures (congestion control schemes, error control schemes, etc.) are required in ATM networks.In this dissertation, we first present an extensive survey of various traffic control schemes and network protocols for ATM networks. In this survey, possible traffic control schemes are examined, and problems of those schemes and their possible solutions are presented. Next, we investigate two key research issues in ATM networks (and other types of high-speed networks): the effects of protocol-processing overhead and the efficiency of traffic control schemes.We first investigate the effects of protocol-processing overhead on the performance of error recovery schemes. Specifically, we investigate the performance trade-offs between link-by-link and edge-to-edge error recovery schemes. Our results show that for a network with high-speed/low-error-rate channels, an edge-to-edge scheme gives a smaller delay than a link-by-link scheme. We then investigate the effectiveness of a priority packet discarding scheme, a congestion control mechanism suitable for high-speed networks. We derive loss probabilities for each stream and investigate the impact of burstiness of traffic streams on the performance of individual streams

Some topics in web performance analysis

This thesis consists of four papers on web performance analysis. In the first paper we investigate the performance of overload control through queue length for two different web server architectures. The simulation result suggests that the benefit of request prioritization is noticeable only when the capacities of the sub-systems match each other. In the second paper we present an M/G/1/K*PS queueing model of a web server. We obtain closed form expressions for web server performance metrics such as average response time, throughput and blocking probability. The model is validated through real measurements. The third paper studies a queueing system with a load balancer and a pool of identical FCFS queues in parallel. By taking the number of servers to infinite, we show that the average waiting time for the system is not always minimized by routing each customer to the expected shortest queue when the information used for decision is stale. In the last paper we consider the problem of admission control to an M/M/1 queue under periodic observations with average cost criterion. The problem is formulated as a discrete time Markov decision process whose states are fully observable. A proof of the existence of the average optimal policy by the vanishing discounted approach is provided. We also show that the optimal policy is nonincreasing with respect to the observed number of customers in the system

Stochastic Dynamic Programming and Stochastic Fluid-Flow Models in the Design and Analysis of Web-Server Farms

A Web-server farm is a specialized facility designed specifically for housing Web servers catering to one or more Internet facing Web sites. In this dissertation, stochastic dynamic programming technique is used to obtain the optimal admission control policy with different classes of customers, and stochastic uid- ow models are used to compute the performance measures in the network. The two types of network traffic considered in this research are streaming (guaranteed bandwidth per connection) and elastic (shares available bandwidth equally among connections). We first obtain the optimal admission control policy using stochastic dynamic programming, in which, based on the number of requests of each type being served, a decision is made whether to allow or deny service to an incoming request. In this subproblem, we consider a xed bandwidth capacity server, which allocates the requested bandwidth to the streaming requests and divides all of the remaining bandwidth equally among all of the elastic requests. The performance metric of interest in this case will be the blocking probability of streaming traffic, which will be computed in order to be able to provide Quality of Service (QoS) guarantees. Next, we obtain bounds on the expected waiting time in the system for elastic requests that enter the system. This will be done at the server level in such a way that the total available bandwidth for the requests is constant. Trace data will be converted to an ON-OFF source and fluid- flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating real data, and the expected waiting time obtained using traditional queueing models. Finally, we consider the network of servers and routers within the Web farm where data from servers flows and merges before getting transmitted to the requesting users via the Internet. We compute the waiting time of the elastic requests at intermediate and edge nodes by obtaining the distribution of the out ow of the upstream node. This out ow distribution is obtained by using a methodology based on minimizing the deviations from the constituent in flows. This analysis also helps us to compute waiting times at different bandwidth capacities, and hence obtain a suitable bandwidth to promise or satisfy the QoS guarantees. This research helps in obtaining performance measures for different traffic classes at a Web-server farm so as to be able to promise or provide QoS guarantees; while at the same time helping in utilizing the resources of the server farms efficiently, thereby reducing the operational costs and increasing energy savings

ComplexWorld Position Paper

The Complex ATM Position Paper is the common research vehicle that defines the high-level, strategic scientific vision for the ComplexWorld Network. The purpose of this document is to provide an orderly and consistent scientific framework for the WP-E complexity theme. The specific objectives of the position paper are to: - analyse the state of the art within the different research areas relevant to the network, identifying the major accomplishments and providing a comprehensive set of references, including the main publications and research projects; - include a complete list of , a list of application topics, and an analysis of which techniques are best suited to each one of those applications; - identify and perform an in-depth analysis of the most promising research avenues and the major research challenges lying at the junction of ATM and complex systems domains, with particular attention to their impact and potential benefits for the ATM community; - identify areas of common interest and synergies with other SESAR activities, with special attention to the research topics covered by other WP-E networks. An additional goal for future versions of this position paper is to develop an indicative roadmap on how these research challenges should be accomplished, providing a guide on how to leverage on different aspects of the complexity research in Air Transport

Air Traffic Control

Improving air traffic control and air traffic management is currently one of the top priorities of the global research and development agenda. Massive, multi-billion euro programs like SESAR (Single European Sky ATM Research) in Europe and NextGen (Next Generation Air Transportation System) in the United States are on their way to create an air transportation system that meets the demands of the future. Air traffic control is a multi-disciplinary field that attracts the attention of many researchers, ranging from pure mathematicians to human factors specialists, and even in the legal and financial domains the optimization and control of air transport is extensively studied. This book, by no means intended to be a basic, formal introduction to the field, for which other textbooks are available, includes nine chapters that demonstrate the multi-disciplinary character of the air traffic control domain