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

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

Exponential Bounds for Queues with Markovian Arrivals

Exponential bounds P[queue ≥ b] ≤ φe^(-γb) are found for queues whose increments are described by Markovian Additive Processes. This is done application of maximal inequalities to exponential martingales for such processes. Through a thermodynamic approach the constant γ is shown to be the decay rate for an asymptotic lower bound for the queue length distribution. The class of arrival processes considered includes a wide variety of Markovian multiplexer models, and a general treatment of these is given, along with that of Markov modulated arrivals. Particular attention is paid to the calculation of the prefactor φ

End-to-End Congestion Control Schemes: Utility Functions, Random Losses and ECN Marks

We present a framework for designing end-to-end congestion control schemes in a network where each user may have a different utility function and may experience noncongestion-related losses. We first show that there exists an additive-increase-multiplicative-decrease scheme using only end-to-end measurable losses such that a socially optimal solution can be reached. We incorporate round-trip delay in this model, and show that one can generalize observations regarding TCP-type congestion avoidance to more general window flow control schemes. We then consider explicit congestion notification (ECN) as an alternate mechanism (instead of losses) for signaling congestion and show that ECN marking levels can be designed to nearly eliminate losses in the network by choosing the marking level independently for each node in the network. While the ECN marking level at each node may depend on the number of flows through the node, the appropriate marking level can be estimated using only aggregate flow measurements, i.e., per-flow measurements are not required

Traffic control mechanisms with cell rate simulation for ATM networks.

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Application of an automatically designed fuzzy logic decision support system to connection admission control in ATM networks

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Transport Control Protocol (TCP) over Optical Burst Switched Networks

Transport Control Protocol (TCP) is the dominant protocol in modern communication networks, in which the issues of reliability, flow, and congestion control must be handled efficiently. This thesis studies the impact of the next-generation bufferless optical burst-switched (OBS) networks on the performance of TCP congestion-control implementations (i.e., dropping-based, explicit-notification-based, and delay-based). The burst contention phenomenon caused by the buffer-less nature of OBS occurs randomly and has a negative impact on dropping-based TCP since it causes a false indication of network congestion that leads to improper reaction on a burst drop event. In this thesis we study the impact of these random burst losses on dropping-based TCP throughput. We introduce a novel congestion control scheme for TCP over OBS networks, called Statistical Additive Increase Multiplicative Decrease (SAIMD). SAIMD maintains and analyzes a number of previous round trip times (RTTs) at the TCP senders in order to identify the confidence with which a packet-loss event is due to network congestion. The confidence is derived by positioning short-term RTT in the spectrum of long-term historical RTTs. The derived confidence corresponding to the packet loss is then taken in to account by the policy developed for TCP congestion-window adjustment. For explicit-notification TCP, we propose a new TCP implementation over OBS networks, called TCP with Explicit Burst Loss Contention Notification (TCP-BCL). We examine the throughput performance of a number of representative TCP implementations over OBS networks, and analyze the TCP performance degradation due to the misinterpretation of timeout and packet-loss events. We also demonstrate that the proposed TCP-BCL scheme can counter the negative effect of OBS burst losses and is superior to conventional TCP architectures in OBS networks. For delay-based TCP, we observe that this type of TCP implementation cannot detect network congestion when deployed over typical OBS networks since RTT fluctuations are minor. Also, delay-based TCP can suffer from falsely detecting network congestion when the underlying OBS network provides burst retransmission and/or deflection. Due to the fact that burst retransmission and deflection schemes introduce additional delays for bursts that are retransmitted or deflected, TCP cannot determine whether this sudden delay is due to network congestion or simply to burst recovery at the OBS layer. In this thesis we study the behaviour of delay-based TCP Vegas over OBS networks, and propose a version of threshold-based TCP Vegas that is suitable for the characteristics of OBS networks. The threshold-based TCP Vegas is able to distinguish increases in packet delay due to network congestion from burst contention at low traffic loads. The evolution of OBS technology is highly coupled with its ability to support upper-layer applications. Without fully understanding the burst transmission behaviour and the associated impact on the TCP congestion-control mechanism, it will be difficult to exploit the advantages of OBS networks fully

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

Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes