Burst switched optical networks supporting legacy and future service types

Focusing on the principles and the paradigm of OBS an overview addressing expectable performance and application issues is presented. Proposals on OBS were published over a decade and the presented techniques spread into many directions. The paper comprises discussions of several challenges that OBS meets, in order to compile the big picture. The OBS principle is presented unrestricted to individual proposals and trends. Merits are openly discussed, considering basic teletraffic theory and common traffic characterisation. A more generic OBS paradigm than usual is impartially discussed and found capable to overcome shortcomings of recent proposals. In conclusion, an OBS that offers different connection types may support most client demands within a sole optical network layer

Frequency Selective Surface Assisted Dynamic Spectrum Access for the Wireless Indoor Environment

This thesis investigates the impact of the use of Frequency Selective Surfaces (FSS) when applied to walls to improve the performance of indoor wireless communications. FSS controlled spectrum sharing is examined using a point-to-point network topology containing two different types of users, intra-room and inter-room, and considers a system with open spectrum access where all users have equal regulatory status. This approach is used together with FSS walls to smartly control resource assignment inside the building. The FSS filter activation threshold is examined, using a threshold value measured from sensing interference in up to three spectrum bands. It is shown how using this threshold, and different FSS state activation strategies, can significantly improve the way an indoor wireless communications system can control its spectrum resources. Different FSS activation strategies are explored. It is shown how the model where a specific value of FSS threshold is set and used throughout shows much better performance compared to situations where the FSS is either continually on or continually off. This performance can be further improved if a more deterministic value is used. This is achieved by using a sliding window average assessment of performance which aims to minimize the frequency of instantaneous FSS states changes; this means a statistical value is used to determine when to activate the FSS. The result shows that a longer sliding window tends to give a better performance for inter-room users without significantly decreasing the performance of intra-room users. An analytical model of system performance using a two-dimensional Markov Chain is developed. Systems with One Available Spectrum (1AS) and Two Available Spectrums (2AS) have been analysed using a state-transition-rate diagram and global equilibrium expressions for both systems are presented

Traffic Characteristics in Corporate Environment

Cieľom práce je analýza dát z pobočkovej telefónnej ústredne VŠB-TUO za časové obdobie desiatich rokov. V prvej časti práce sú popísané teoretické poznatky o obsluhe a teória využitých funkcií. Praktická časť mojej práce sa zameriava na vytvorenie programu v programovacom jazyku Python, ktorý spracuváva dataset, umožní tým jeho detailnú analýzu a aplikáciu modelu Erlang B a Engset. Práca obsahuje radu analýz a rôznych štatistík týkajúcich sa prevádzky pobočkovej ústredne.The aim of this thesis is to analyse data over the period 10 years from the VSB-TUO private branch exchange. The first section focuses on theoretic basics of queuing theory. The practical aspect of my work aims to create a program in the Python programming language. It processes a dataset, which enables a deeper analysis of the dataset with applying models Erlang B and Engset. The thesis includes a detailed analysis of the private branch exchange operation as well as other statistics concerning it.440 - Katedra telekomunikační technikyvýborn

Quantum Reinforcement Learning for Dynamic Spectrum Access in Cognitive Radio Networks

Abstract This thesis proposes Quantum Reinforcement Learning (QRL) as an improvement to conventional reinforcement learning-based dynamic spectrum access used within cognitive radio networks. The aim is to overcome the slow convergence problem associated with exploration within reinforcement learning schemes. A literature review for the background of the carried out research work is illustrated. Review of research works on learning-based assignment techniques as well as quantum search techniques is provided. Modelling of three traditional dynamic channel assignment techniques is illustrated and the advantage characteristic of each technique is discussed. These techniques have been simulated to provide a comparison with learning based techniques, including QRL. Reinforcement learning techniques are used as a direct comparison with the Quantum Reinforcement Learning approaches. The elements of Quantum computation are then presented as an introduction to quantum search techniques. The Grover search algorithm is introduced. The algorithm is discussed from a theoretical perspective. The Grover algorithm is then used for the first time as a spectrum allocation scheme and compared to conventional schemes. Quantum Reinforcement Learning (QRL) is introduced as a natural evolution of the quantum search. The Grover search algorithm is combined as a decision making mechanism with conventional Reinforcement Learning (RL) algorithms resulting in a more efficient learning engine. Simulation results are provided and discussed. The convergence speed has been significantly increased. The beneficial effects of Quantum Reinforcement Learning (QRL) become more pronounced as the traffic load increases. The thesis shows that both system performance and capacity can be improved. Depending on the traffic load, the system capacity has improved by 9-84% from a number of users supported perspective. It also demonstrated file delay reduction for up to an average of 26% and 2.8% throughput improvement

Loss-free architectures in optical burst switched networks for a reliable and dynamic optical layer

For the last three decades, the optical fiber has been a quite systematic response to dimensioning issues in the Internet. Originally restricted to long haul networks, the optical network has gradually descended the network hierarchy to discard the bottlenecks. In the 90's, metropolitan networks became optical. Today, optical fibers are deployed in access networks and reach the users. In a near future, besides wireless access and local area networks, all networks in the network hierarchy may be made of fibers, in order to support current services (HDTV) and the emergence of new applications (3D-TV newly commercialized in USA). The deployment of such greedy applications will initiate an upward upgrade. The first step may be the Metropolitan Area Networks (MANs), not only because of the traffic growth, but also because of the variety of served applications, each with a specific traffic profile. The current optical layer is of mitigated efficiency, dealing with unforeseen events. The lack of reactivity is mainly due to the slow switching devices: any on-line decision of the optical layer is delayed by the configuration of the. devices. When the optical network has been extended in the MANs, a lot of efforts has been deployed to improve the reactivity of the optical layer. The Optical Circuit Switching paradigm (OCS) has been improved but it ultimately relies on off-line configuration of the optical devices. Optical Burst Switching (OBS) can be viewed as a highly flexible evolution of OCS, that operates five order of magnitude faster. Within this 'architecture, the loss-free guaranty can be abandoned in order to improve the reactivity of the optical layer. Indeed, reliability and reactivity appear as antagonists properties and getting closer to either of them mitigates the other. This thesis aims at proposing a solution to achieve reliable transmission over a dynamic optical layer. Focusing on OBS networks, our objective is to solve the contention issue without mitigating the reactivity. After the consideration of contention avoidance mechanisms with routing constraints similar as in OCS networks, we investigate the reactive solutions that intend to solve the contentions. None of the available contention resolution scheme can ensure the 100% efficiency that leads to loss-free transmission. An attractive solution is the recourse to electrical buffering, but it is notoriously disregarded because (1) it may highly impact the delays and (2) loss can occur due to buffer overflows. The efficiency of translucent architectures thus highly depends on the buffer availability, that can be improved by reducing the time spent in the buffers and the contention rate. We show that traffic grooming can highly reduce the emission delay, and consequently the buffer occupancy. In a first architecture, traffic grooming is enabled by a translucent core node architecture, capable to re-aggregate incoming bursts. The re-aggregation is mandatory to "de-groom" the bursts in the core network (i.e., to demultiplex the content of a burst). On the one hand, the re-aggregation highly reduces the loss probability, but on the other hand, it absorbs the benefits of traffic grooming. Finally, dynamic access to re-aggregation for contention resolution, despite the significant reduction of the contention rate, dramatically impacts the end-to-end delay and the memory requirement. We thus propose a second architecture, called CAROBS, that exploits traffic grooming in the optical domain. This framework is fully dynamic and can be used jointly with our translucent architecture that performs re-aggregation. As the (de)grooming operations do not involve re-aggregation, the translucent module can be restricted to contention resolution. As a result, the volume of data submitted to re-aggregation is drastically reduced and loss-free transmission can be reached with the same reactivity, end-to-end delay and memory requirement as a native OBS networ

Introduction to Queueing Theory and Stochastic Teletraffic Models

The aim of this textbook is to provide students with basic knowledge of stochastic models that may apply to telecommunications research areas, such as traffic modelling, resource provisioning and traffic management. These study areas are often collectively called teletraffic. This book assumes prior knowledge of a programming language, mathematics, probability and stochastic processes normally taught in an electrical engineering course. For students who have some but not sufficiently strong background in probability and stochastic processes, we provide, in the first few chapters, background on the relevant concepts in these areas.Comment: 298 page

Comparative analysis of power consumption in asynchronous wavelength modular optical switching fabrics

Next-generation optical routers will be designed to support the flexibility required by Future Internet services and, at the same time, to overcome the power consumption bottleneck which appears to limit throughput scalability in today routers. A model to evaluate average power consumption in asynchronous optical switching fabrics is here presented to compare these architectures with other synchronous and asynchronous solutions. The combination of wavelength modular switching fabrics with low spatial complexity and asynchronous operation is demonstrated to be the most power-efficient solution among those considered which employ wavelength converters, through presentation and discussion of a thorough set of numerical results. © 2011 Elsevier B.V. All rights reserved