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

A Bio-Inspired Two-Layer Mixed-Signal Flexible Programmable Chip for Early Vision

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.Office of Naval Research (USA) N-000140210884European Commission IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

APPLICATION OF BIFURCATION THEORY TO CURRENT MODE CONTROLLED PARALLEL-CONNECTED BOOST DC-DC CONVERTERS

This project is to design a circuit which will guarantee stable operation at switching frequencies, and any quasi-periodic or chaotic operation is regarded as being undesirable and should be avoided. This project focuses in particular on the application of bifurcation theory to parallel-input / parallel-output two-module current-programmed DC-DC converters. Besides, this project describes the operation of Current Mode Controlled Parallel-Connected Boost DC-DC Converters and basically defines chaos, bifurcation and quasi-periodic distortion of the circuit by varying the reference current and comparing it with inductor output current. Within specific ranges of reference current the circuit operates without any distortion. The design includes the simulation of any bifurcation within the intended operation range by using PSpice, Multisim and EWB software. The inductor current output waveforms obtained and compared at different levels of reference currents. There are few ways to improve the output waveforms such as connecting freewheeling diode with parallel to inductor, using combination of triple input/triple output Current Mode Controlled converter or just using parallel input/series output configuration. Parallel-input / paralleloutput are the most common configuration that can be used in current mode control DC-DC converters. Simulation and calculation results shows that capacitor voltage ripple factor reduced from 30% to 3%(actual) and output current ripple from 20% to 3%. Improvement in this type of converter will open up new applications in datacommunication, telecommunication, power-supply in PC and inside the notebook, industrial automation and so forth. The core of the project work focuses on simulating the entire process and later building the prototype

The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Cell assembly dynamics of sparsely-connected inhibitory networks: a simple model for the collective activity of striatal projection neurons

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices [Carrillo-Reid et al., J. Neurophysiology 99 (2008) 1435{1450]. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We found that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal [Ponzi and Wickens, PLoS Comp Biol 9 (2013) e1002954] that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.Comment: 22 pages, 9 figure

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

Co-evolution and networks adaptation.

What is the role of co-evolution in the adaptation of a population of firms to a hostile environment ? To answer this question, we revisit network sociology starting from Kauffman s biological computer model. We apply a qualitative methodology to update exploitation and exploration mechanisms in nine Japanese interfirm networks. From these results, this article draws a typology of the adaptation forms, distinguishing pack, migratory, herd and colony networks.Sociologie des organisations; Réseaux d’entreprises;

A fibre-based single-photon source

The controlled emission and absorption of single photons is an important enabling technology in the fields of quantum communication, cryptography and computing. We have realised a novel single photon source, based on a miniature ‘endcap’ ion trap with integrated optical fibres. To minimise distortion of the trapping field the fibres are tightly integrated and recessed within the two hollow cylindrical rf electrodes of the trap. This allows us to bring the fibres to within approximately 300 μm of the trapped ion. With the fibres in place we are able to collect the ion’s fluorescence using no further optics. In this thesis the ion trap is fully characterised, and the quantum nature of the light demonstrated in the results of a variant on the Hanbury Brown-Twiss photon-correlation experiment. The scheme will ultimately be extended to implement a coherent ion-photon interface through strong coupling cavity-QED. Towards this end, an ultra-high-finesse cavity has been designed and fabricated by laser-machining and coating surfaces with a range of radii of curvature on the end facets of the fibres. To improve the stability and precision manipulation of the cavity in-vacuum, an entirely new trap has been designed and built. Finally, the current status of the fibre cavity and the outlook for the experiment are presented