1,618 research outputs found

    Fast simulation of the leaky bucket algorithm

    Get PDF
    We use fast simulation methods, based on importance sampling, to efficiently estimate cell loss probability in queueing models of the Leaky Bucket algorithm. One of these models was introduced by Berger (1991), in which the rare event of a cell loss is related to the rare event of an empty finite buffer in an "overloaded" queue. In particular, we propose a heuristic change of measure for importance sampling to efficiently estimate the probability of the rare empty-buffer event in an asymptotically unstable GI/GI/1/k queue. This change of measure is, in a way, "dual" to that proposed by Parekh and Walrand (1989) to estimate the probability of a rare buffer overflow event. We present empirical results to demonstrate the effectiveness of our fast simulation method. Since we have not yet obtained a mathematical proof, we can only conjecture that our heuristic is asymptotically optimal, as k/spl rarr//spl infin/

    Electronic and photonic switching in the atm era

    Get PDF
    Broadband networks require high-capacity switches in order to properly manage large amounts of traffic fluxes. Electronic and photonic technologies are being used to achieve this objective both allowing different multiplexing and switching techniques. Focusing on the asynchronous transfer mode (ATM), the inherent different characteristics of electronics and photonics makes different architectures feasible. In this paper, different switching structures are described, several ATM switching architectures which have been recently implemented are presented and the implementation characteristics discussed. Three diverse points of view are given from the electronic research, the photonic research and the commercial switches. Although all the architectures where successfully tested, they should also follow different market requirements in order to be commercialised. The characteristics are presented and the architectures projected over them to evaluate their commercial capabilities.Peer ReviewedPostprint (published version

    An Adaptive Scheme for Admission Control in ATM Networks

    Get PDF
    This paper presents a real time front-end admission control scheme for ATM networks. A call management scheme which uses the burstiness associated with traffic sources in a heterogeneous ATM environment to effect dynamic assignment of bandwidth is presented. In the proposed scheme, call acceptance is based on an on-line evaluation of the upper bound on cell loss probability which is derived from the estimated distribution of the number of calls arriving. Using this scheme, the negotiated quality of service will be assured when there is no estimation error. The control mechanism is effective when the number of calls is large, and tolerates loose bandwidth enforcement and loose policing control. The proposed approach is very effective in the connection oriented transport of ATM networks where the decision to admit new traffic is based on thea priori knowledge of the state of the route taken by the traffic

    DTMsim - DTM channel simulation in ns

    Get PDF
    Dynamic Transfer Mode (DTM) is a ring based MAN technology that provides a channel abstraction with a dynamically adjustable capacity. TCP is a reliable end to end transport protocol capable of adjusting its rate. The primary goal of this work is investigate the coupling of dynamically allocating bandwidth to TCP flows with the affect this has on the congestion control mechanism of TCP. In particular we wanted to find scenerios where this scheme does not work, where either all the link capacity is allocated to TCP or congestion collapse occurs and no capacity is allocated to TCP. We have created a simulation environment using ns-2 to investigate TCP over networks which have a variable capacity link. We begin with a single TCP Tahoe flow over a fixed bandwidth link and progressively add more complexity to understand the behaviour of dynamically adjusting link capacity to TCP and vice versa

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

    Get PDF
    SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    Quality of service over ATM networks

    Get PDF
    PhDAbstract not availabl

    Energy-efficient wireless communication

    Get PDF
    In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

    Some aspects of traffic control and performance evaluation of ATM networks

    Get PDF
    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
    corecore