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

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

Operating-system support for distributed multimedia

Multimedia applications place new demands upon processors, networks and operating systems. While some network designers, through ATM for example, have considered revolutionary approaches to supporting multimedia, the same cannot be said for operating systems designers. Most work is evolutionary in nature, attempting to identify additional features that can be added to existing systems to support multimedia. Here we describe the Pegasus project's attempt to build an integrated hardware and operating system environment from\ud the ground up specifically targeted towards multimedia

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 Slotted Ring Test Bed for the Study of ATM Network Congestion Management

This thesis addresses issues raised by the proposed Broadband Integrated Services Digital Network which will provide a flexible combination of integrated services traffic through its cell-based Asynchronbus Transport Mode (ATM). The introduction of a cell-based, connection-oriented, transport mode brings with it new technical challenges for network management. The routing of cells, their service at switching centres, and problems of cell congestion not encountered in the existing network, are some of the key issues. The thesis describes the development of a hardware slotted ring testbed for the investigation of congestion management in an ATM network. The testbed is designed to incorporate a modified form of the ORWELL protocol to control media access. The media access protocol is analysed to give a model for maximum throughput and reset interval under various traffic distributions. The results from the models are compared with measurements carried out on the testbed, where cell arrival statistics are also varied. It is shown that the maximum throughput of the testbed is dependent on both traffic distribution and cell arrival statistics. The testbed is used for investigations in a heterogeneous traffic environment where two classes of traffic with different cell arrival statistics and quality of service requirements are defined. The effect of prioritisation, media access protocol, traffic intensity, and traffic source statistics were investigated by determining an Admissible Load Region (ALR) for a network station. Conclusions drawn from this work suggest that there are many problems associated with the reliable definition of an ALR because of the number of variable parameters which could shift the ALR boundary. A suggested direction for further work is to explore bandwidth reservation and the concept of equivalent capacity of a connection, and how this can be linked to source control parameters

Video traffic modeling and delivery

Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

Performance analysis of an ATM network with multimedia traffic: a simulation study

Traffic and congestion control are important in enabling ATM networks to maintain the Quality of Service (QoS) required by end users. A Call Admission Control (CAC) strategy ensures that the network has sufficient resources available at the start of each call, but this does not prevent a traffic source from violating the negotiated contract. A policing strategy (User Parameter Control (UPC)) is also required to enforce the negotiated rates for a particular connection and to protect conforming users from network overload. The aim of this work is to investigate traffic policing and bandwidth management at the User to Network Interface (UNI). A policing function is proposed which is based on the leaky bucket (LB) which offers improved performance for both real time (RT) traffic such as speech and video and non-real time (non-RT) traffic, mainly data by taking into account the QoS requirements. A video cell in violation of the negotiated bit rate causes the remainder of the slice to be discarded. This 'tail clipping' provides protection for the decoder from damaged video slices. Speech cells are coded using a frequency domain coder, which places the most significant bits of a double speech sample into a high priority cell and the least significant bits into a high priority cell. In the case of congestion, the low priority cell can be discarded with little impact on the intelligibility of the received speech. However, data cells require loss-free delivery and are buffered rather than being discarded or tagged for subsequent deletion. This triple strategy is termed the super leaky bucket (SLB). Separate queues for RT and non-RT traffic, are also proposed at the multiplexer, with non pre-emptive priority service for RT traffic if the queue exceeds a predetermined threshold. If the RT queue continues to grow beyond a second threshold, then all low priority cells (mainly speech) are discarded. This scheme protects non-RT traffic from being tagged and subsequently discarded, by queueing the cells and also by throttling back non-RT sources during periods of congestion. It also prevents the RT cells from being delayed excessively in the multiplexer queue. A simulation model has been designed and implemented to test the proposal. Realistic sources have been incorporated into the model to simulate the types of traffic which could be expected on an ATM network. The results show that the S-LB outperforms the standard LB for video cells. The number of cells discarded and the resulting number of damaged video slices are significantly reduced. Dual queues with cyclic service at the multiplexer also reduce the delays experienced by RT cells. The QoS for all categories of traffic is preserved

Traffic control mechanisms with cell rate simulation for ATM networks.

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