On-board congestion control for satellite packet switching networks

It is desirable to incorporate packet switching capability on-board for future communication satellites. Because of the statistical nature of packet communication, incoming traffic fluctuates and may cause congestion. Thus, it is necessary to incorporate a congestion control mechanism as part of the on-board processing to smooth and regulate the bursty traffic. Although there are extensive studies on congestion control for both baseband and broadband terrestrial networks, these schemes are not feasible for space based switching networks because of the unique characteristics of satellite link. Here, we propose a new congestion control method for on-board satellite packet switching. This scheme takes into consideration the long propagation delay in satellite link and takes advantage of the the satellite's broadcasting capability. It divides the control between the ground terminals and satellite, but distributes the primary responsibility to ground terminals and only requires minimal hardware resource on-board satellite

Adaptive Neural Network Controller for ATM Traffic

Broadband-Integrated Services Digital Networks (B-ISDN), along with Asynchronous Transfer Mode (ATM), were designed to meet the requirements of modern communication networks to handle multiple users and a wide variety of diverse traffic including voice, data and video. ATM responds to requests for admission to the network by analyzing whether or not the grade of service (GOS) requirement, specified in the admission request, can be guaranteed without violating the GOS guaranteed to traffic already accepted into the network. The GOS is typically a parameter such as cell loss rate (CLR), average delay, or some other measurement associated with network performance. In order to develop a tractable mathematical algorithm for controlling admission, an accurate model of the communication network and traffic in question is necessary. The complex and dynamic nature of these communication networks make them very difficult to model. Even when such a model can be developed, often with unrealistic simplifications or unsupportable assumptions, the associated mathematical algorithm is frequently excessively cumbersome and timely processing of an admission request is lost. An alternative to conventional mathematical algorithms for cases like these is the use of neural networks (NN). NNs can learn complicated functions relating the inputs and outputs of a system without prior knowledge about the system itself. For ATM B-ISDN networks, NNs can learn the function relating input traffic parameters and resulting network performance by training on an appropriate set of traffic parameter inputs and resulting GOS outputs. In this work three neural network admission controller schemes are examined. The Bayes error rate, as bounded by the Parzen window technique, is also introduced as a benchmark for measuring the performance of these admission controllers

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

Resource management for multimedia traffic over ATM broadband satellite networks

PhDAbstract not availabl

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

An efficient flow control algorithm for multi-rate multicast networks

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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

Adaptive technique for ATM call admission and routing control using traffic prediction by neural networks

This paper discusses a technique for call admission and routing control, based on a global quality function, which is dependent on the allocated bandwidth, the free network capacity and the call rejection rate, and incorporates quality of service functions, predicted by neural networks. The superior capability of this technique to support admission and routing decisions, according to the characteristics of the traffic generated by admitted calls, is demonstrated by simulation results carried out using suitable traffic and network models, which are equally discussed. It is also shown that the proposed technique, being based on several observed traffic parameters, offers better results than methods based only on declared bandwidth parameters

Flow control in connection-oriented networks: a time-varying sampling period system case study

summary:In this paper congestion control problem in connection-oriented communication network with multiple data sources is addressed. In the considered network the feedback necessary for the flow regulation is provided by means of management units, which are sent by each source once every M data packets. The management units, carrying the information about the current network state, return to their origin round trip time RTT after they were sent. Since the source rate is adjusted only at the instant of the control units arrival, the period between the transfer speed modifications depends on the flow rate RTT earlier, and consequently varies with time. A new, nonlinear algorithm combining the Smith principle with the proportional controller with saturation is proposed. Conditions for data loss elimination and full resource utilisation are formulated and strictly proved with explicit consideration of irregularities in the feedback information availability. Subsequently, the algorithm robustness with respect to imprecise propagation time estimation is demonstrated. Finally, a modified strategy implementing the feed-forward compensation is proposed. The strategy not only eliminates packet loss and guarantees the maximum resource utilisation, but also decreases the influence of the available bandwidth on the queue length. In this way the data transfer delay jitter is reduced, which helps to obtain the desirable Quality of Service (QoS) in the network