On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices

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

Explicit congestion control algorithms for available bit rate services in asynchronous transfer mode networks

Congestion control of available bit rate (ABR) services in asynchronous transfer mode (ATM) networks has been the recent focus of the ATM Forum. The focus of this dissertation is to study the impact of queueing disciplines on ABR service congestion control, and to develop an explicit rate control algorithm. Two queueing disciplines, namely, First-In-First-Out (FIFO) and per-VC (virtual connection) queueing, are examined. Performance in terms of fairness, throughput, cell loss rate, buffer size and network utilization are benchmarked via extensive simulations. Implementation complexity analysis and trade-offs associated with each queueing implementation are addressed. Contrary to the common belief, our investigation demonstrates that per-VC queueing, which is costlier and more complex, does not necessarily provide any significant improvement over simple FIFO queueing. A new ATM switch algorithm is proposed to complement the ABR congestion control standard. The algorithm is designed to work with the rate-based congestion control framework recently recommended by the ATM Forum for ABR services. The algorithm\u27s primary merits are fast convergence, high throughput, high link utilization, and small buffer requirements. Mathematical analysis is done to show that the algorithm converges to the max-min fair allocation rates in finite time, and the convergence time is proportional to the distinct number of fair allocations and the round-trip delays in the network. At the steady state, the algorithm operates without causing any oscillations in rates. The algorithm does not require any parameter tuning, and proves to be very robust in a large ATM network. The impact of ATM switching and ATM layer congestion control on the performance of TCP/IP traffic is studied and the results are presented. The study shows that ATM layer congestion control improves the performance of TCP/IP traffic over ATM, and implementing the proposed switch algorithm drastically reduces the required switch buffer requirements. In order to validate claims, many benchmark ATM networks are simulated, and the performance of the switch is evaluated in terms of fairness, link utilization, response time, and buffer size requirements. In terms of performance and complexity, the algorithm proposed here offers many advantages over other proposed algorithms in the literature

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

Information Switching Processor (ISP) contention analysis and control

Future satellite communications, as a viable means of communications and an alternative to terrestrial networks, demand flexibility and low end-user cost. On-board switching/processing satellites potentially provide these features, allowing flexible interconnection among multiple spot beams, direct to the user communications services using very small aperture terminals (VSAT's), independent uplink and downlink access/transmission system designs optimized to user's traffic requirements, efficient TDM downlink transmission, and better link performance. A flexible switching system on the satellite in conjunction with low-cost user terminals will likely benefit future satellite network users

Joint buffer management and scheduling for input queued switches

Input queued (IQ) switches are highly scalable and they have been the focus of many studies from academia and industry. Many scheduling algorithms have been proposed for IQ switches. However, they do not consider the buffer space requirement inside an IQ switch that may render the scheduling algorithms inefficient in practical applications. In this dissertation, the Queue Length Proportional (QLP) algorithm is proposed for IQ switches. QLP considers both the buffer management and the scheduling mechanism to obtain the optimal allocation region for both bandwidth and buffer space according to real traffic load. In addition, this dissertation introduces the Queue Proportional Fairness (QPF) criterion, which employs the cell loss ratio as the fairness metric. The research in this dissertation will show that the utilization of network resources will be improved significantly with QPF. Furthermore, to support diverse Quality of Service (QoS) requirements of heterogeneous and bursty traffic, the Weighted Minmax algorithm (WMinmax) is proposed to efficiently and dynamically allocate network resources. Lastly, to support traffic with multiple priorities and also to handle the decouple problem in practice, this dissertation introduces the multiple dimension scheduling algorithm which aims to find the optimal scheduling region in the multiple Euclidean space

Performance Analysis of an ATM MUX with a New Space Priority Mechanism under ON-OFF Arrival Processes

Abstract: We propose a new space priority mechanism, and analyze its performance in a single Constant Bit Rate (CBR) server. The arrival process is derived from the superposition of two types of traffics, each in turn results from the superposition of homogeneous ON-OFF sources that can be approximated by means of a two-state Markov Modulated Poisson Process (MMPP). The buffer mechanism enables the Asynchronous Transfer Mode (ATM) layer to adapt the quality of the cell transfer to the Quality of Service (QoS) requirements and to improve the utilization of network resources. This is achieved by "Selective-Delaying and Pushing-In" (SDPI) cells according to the class they belong to. The scheme is applicable to schedule delay-tolerant non-real time traffic and delaysensitive real time traffic. Analytical expressions for various performance parameters and numerical results are obtained. Simulation results in term of cell loss probability conform with our numerical analysis