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

Virtual path bandwidth distribution and capacity allocation with bandwidth sharing

Broadband high-speed networks, such as B-ISDN, are expected to play a dominant role in the future of networking due to their capability to service a variety of traffic types with very different bandwidth requirements such as video, voice and data. to increase network efficiency in B-ISDN and other such connection oriented networks, the concept of a virtual path (VP) has been proposed and studied in the literature. A VP is a permanent or semi-permanent reservation of capacity between two nodes. Using VPs can potentially reduce call setup delays, simplify hardware, provide quality of service performance guarantees, and reduce disruption in the event of link or node failure.;In order to use VPs efficiently, two problems must be solved. With the objective of optimizing network performance, (1) the VPs must be placed within the network, and (2) network link capacity must be divided among the VPs. Most previous work aimed at solving these problems has focused on one problem in isolation of the other. at the same time, previous research efforts that have considered the joint solution of these problems have considered only restricted cases. In addition, these efforts have not explicitly considered the benefits of sharing bandwidth among VPs in the network.;We present a heuristic solution method for the joint problem of virtual path distribution and capacity allocation without many of the limitations found in previous studies. Our solution method considers the joint bandwidth allocation and VP placement problem and explicitly considers the benefits of shared bandwidth. We demonstrate that our algorithm out-performs previous algorithms in cases where network resources are limited. Because our algorithm provides shared bandwidth, solutions found by our algorithm will have a lower setup probability than a network that does not use VPs as well as a lower loss probability than provided by VPDBA solutions produced by previous algorithms. In addition, our algorithm provides fairness not found in solutions produced by other algorithms by guaranteeing that some service will be provided to each source-destination pair within the network

Statistical characterisation and stochastic modelling of 1-layer variable bit rate H.261 video codec traffic

The Integrated Services Digital Network(ISDN) is under re-design to provide flexibility which will ensure efficient network utilisation in the provision of broadband services. The main broadband services envisaged for provision on the Broadband ISDN(B-ISDN) are : Videophone; Videoconferencing; Television and High Definition TV. The B-ISDN will be a packet switched network where the packets(cells) will be transferred by the Asynchronous Transfer Mode(ATM) concept. Unlike voice and data services, the impact video services will have on the BISDN is unknown and hence loss of information is difficult to predict. Present videophone terminals are based on the CCITT H.261 Video Coding standard hence the picture quality is variable because video codec traffic is transmitted at a constant rate. To maintain a constant quality picture the codec output data must be transmitted at a variable rate or alternatively, for constant rate video codecs extra information must be made available to achieve constant picture quality. This latter technique is 2- Layer video coding where the first layer transmits at a constant rate and the second layer at a variable rate. The ATM B-ISDN promises constant picture quality video services, therefore to achieve this aim the impact variable rate video sources will have on the network must be determined by network simulation, thus variable rate video source models must be derived. To statistically characterise and stochastically model 1-Layer VBR(Variable Bit Rate) H.261 Video Codec traffic, here a videophone sequence is analysed by two alternative strategies : Talk-Listen and Motion Level. This analysis also found that 2-Layer H.261 Video Codec traffic can be stochastically modelled via a 1-Layer VBR H.261 Video Codec traffic model. Numerous hierarchical stochastic models with the ability to capture the statistical characteristics of long video sequences, in particular the short-term and long-term autocorrelations, are presented. One such model was simulated and the resulting simulated traffic was analysed to confirm the advantage hierarchical stochastic models have over non-hierarchical stochastic models in modelling video source traffic

Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

Survivable mesh-network design & optimization to support multiple QoP service classes

Every second, vast amounts of data are transferred over communication systems around the world, and as a result, the demands on optical infrastructures are extending beyond the traditional, ring-based architecture. The range of content and services available from the Internet is increasing, and network operations are constantly under pressure to expand their optical networks in order to keep pace with the ever increasing demand for higher speed and more reliable links

Resource Allocation in Next Generation Mobile Networks

The increasing heterogeneity of the mobile network infrastructure together with the explosively growing demand for bandwidth-hungry services with diverse quality of service (QoS) requirements leads to a degradation in the performance of traditional networks. To address this issue in next-generation mobile networks (NGMN), various technologies such as software-defined networking (SDN), network function virtualization (NFV), mobile edge/cloud computing (MEC/MCC), non-terrestrial networks (NTN), and edge ML are essential. Towards this direction, an optimal allocation and management of heterogeneous network resources to achieve the required low latency, energy efficiency, high reliability, enhanced coverage and connectivity, etc. is a key challenge to be solved urgently. In this dissertation, we address four critical and challenging resource allocation problems in NGMN and propose efficient solutions to tackle them. In the first part, we address the network slice resource provisioning problem in NGMN for delivering a wide range of services promised by 5G systems and beyond, including enhanced mobile broadband (eMBB), ultra-reliable and low latency (URLLC), and massive machine-type communication (mMTC). Network slicing is one of the major solutions needed to meet the differentiated service requirements of NGMN, under one common network infrastructure. Towards robust mobile network slicing, we propose a novel approach for the end-to-end (E2E) resource allocation in a realistic scenario with uncertainty in slices' demands using stochastic programming. The effectiveness of our proposed methodology is validated through simulations. Despite the significant benefits that network slicing has demonstrated to bring to the management and performance of NGMN, the real-time response required by many emerging delay-sensitive applications, such as autonomous driving, remote health, and smart manufacturing, necessitates the integration of multi-access edge computing (MEC) into network sliding for 5G networks and beyond. To this end, we discuss a novel collaborative cloud-edge-local computation offloading scheme in the next two parts of this dissertation. The first part studies the problem from the perspective of the infrastructure provider and shows the effectiveness of the proposed approach in addressing the rising number of latency-sensitive services and improving energy efficiency which has become a primary concern in NGMN. Moreover, taking into account the perspective of application (higher layer), we propose a novel framework for the optimal reservation of resources by applications, resulting in significant resource savings and reduced cost. The proposed method utilizes application-specific resource coupling relationships modeled using linear regression analysis. We further improve this approach by using Reinforcement Learning to automatically derive resource coupling functions in dynamic environments. Enhanced connectivity and coverage are other key objectives of NGMN. In this regard, unmanned aerial vehicles (UAVs) have been extensively utilized to provide wireless connectivity in rural and under-developed areas, enhance network capacity, and provide support for peaks or unexpected surges in user demand. The popularity of UAVs in such scenarios is mainly owing to their fast deployment, cost-efficiency, and superior communication performance resulting from line-of-sight (LoS)-dominated wireless channels. In the fifth part of this dissertation, we formulate the problem of aerial platform resource allocation and traffic routing in multi-UAV relaying systems wherein UAVs are deployed as flying base stations. Our proposed solution is shown to improve the supported traffic with minimum deployment cost. Moreover, the new breed of intelligent devices and applications such as UAVs, AR/VR, remote health, autonomous vehicles, etc. requires a novel paradigm shift from traditional cloud-based learning to a distributed, low-latency, and reliable ML at the network edge. To this end, Federated Learning (FL) has been proposed as a new learning scheme that enables devices to collaboratively learn a shared model while keeping the training data locally. However, the performance of FL is significantly affected by various security threats such as data and model poisoning attacks. Towards reliable edge learning, in the last part of this dissertation, we propose trust as a metric to measure the trustworthiness of the FL agents and thereby enhance the reliability of FL

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

NASA Space Engineering Research Center Symposium on VLSI Design

The NASA Space Engineering Research Center (SERC) is proud to offer, at its second symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories and the electronics industry. These featured speakers share insights into next generation advances that will serve as a basis for future VLSI design. Questions of reliability in the space environment along with new directions in CAD and design are addressed by the featured speakers