Stochastische Analyse und lernbasierte Algorithmen zur Ressourcenbereitstellung in optischen Netzwerken

The unprecedented growth in Internet traffic has driven the innovations in provisioning of optical resources as per the need of bandwidth demands such that the resource utilization and spectrum efficiency could be maximized. With the advent of the next generation flexible optical transponders and switches, the flexible-grid-based elastic optical network (EON) is foreseen as an alternative to the widely deployed fixed-grid-based wavelength division multiplexing networks. At the same time, the flexible resource provisioning also raises new challenges for EONs. One such challenge is the spectrum fragmentation. As network traffic varies over time, spectrum gets fragmented due to the setting up and tearing down of non-uniform bandwidth requests over aligned (i.e., continuous) and adjacent (i.e., contiguous) spectrum slices, which leads to a non-optimal spectrum allocation, and generally results in higher blocking probability and lower spectrum utilization in EONs. To address this issue, the allocation and reallocation of optical resources are required to be modeled accurately, and managed efficiently and intelligently. The modeling of routing and spectrum allocation in EONs with the spectrum contiguity and spectrum continuity constraints is well-investigated, but existing models do not consider the fragmentation issue resulted by these constraints and non-uniform bandwidth demands. This thesis addresses this issue and considers both the constraints to computing exact blocking probabilities in EONs with and without spectrum conversion, and with spectrum reallocation (known as defragmentation) for the first time using the Markovian approach. As the exact network models are not scalable with respect to the network size and capacity, this thesis proposes load-independent and load-dependent approximate models to compute approximate blocking probabilities in EONs. Results show that the connection blocking due to fragmentation can be reduced by using a spectrum conversion or a defragmentation approach, but it can not be eliminated in a mesh network topology. This thesis also deals with the important network resource provisioning task in EONs. To this end, it first presents algorithmic solutions to efficiently allocate and reallocate spectrum resources using the fragmentation factor along spectral, time, and spatial dimensions. Furthermore, this thesis highlights the role of machine learning techniques in alleviating issues in static provisioning of optical resources, and presents two use-cases: handling time-varying traffic in optical data center networks, and reducing energy consumption and allocating spectrum proportionately to traffic classes in fiber-wireless networks.Die flexible Nutzung des Spektrums bringt in Elastischen Optischen Netze (EON) neue Herausforderungen mit sich, z.B., die Fragmentierung des Spektrums. Die Fragmentierung entsteht dadurch, dass die Netzwerkverkehrslast sich im Laufe der Zeit ändert und so wird das Spektrum aufgrund des Verbindungsaufbaus und -abbaus fragmentiert. Das für eine Verbindung notwendige Spektrum wird durch aufeinander folgende (kontinuierliche) und benachbarte (zusammenhängende) Spektrumsabschnitte (Slots) gebildet. Dies führt nach den zahlreichen Reservierungen und Freisetzungen des Spektrums zu einer nicht optimalen Zuordnung, die in einer höheren Blockierungs-wahrscheinlichkeit der neuen Verbindungsanfragen und einer geringeren Auslastung von EONs resultiert. Um dieses Problem zu lösen, müssen die Zuweisung und Neuzuordnung des Spektrums in EONs genau modelliert und effizient sowie intelligent verwaltet werden. Diese Arbeit beschäftigt sich mit dem Fragmentierungsproblem und berücksichtigt dabei die beiden Einschränkungen: Kontiguität und Kontinuität. Unter diesen Annahmen wurden analytische Modelle zur Berechnung einer exakten Blockierungswahrscheinlichkeit in EONs mit und ohne Spektrumskonvertierung erarbeitet. Außerdem umfasst diese Arbeit eine Analyse der Blockierungswahrscheinlichkeit im Falle einer Neuzuordnung des Sprektrums (Defragmentierung). Diese Blockierungsanalyse wird zum ersten Mal mit Hilfe der Markov-Modelle durchgeführt. Da die exakten analytischen Modelle hinsichtlich der Netzwerkgröße und -kapazität nicht skalierbar sind, werden in dieser Dissertation verkehrslastunabhängige und verkehrslastabhängige Approximationsmodelle vorgestellt. Diese Modelle bieten eine Näherung der Blockierungswahrscheinlichkeiten in EONs. Die Ergebnisse zeigen, dass die Blockierungswahrscheinlichkeit einer Verbindung aufgrund von einer Fragmentierung des Spektrums durch die Verwendung einer Spektrumkonvertierung oder eines Defragmentierungsverfahrens verringert werden kann. Eine effiziente Bereitstellung der optischen Netzwerkressourcen ist eine wichtige Aufgabe von EONs. Deswegen befasst sich diese Arbeit mit algorithmischen Lösungen, die Spektrumressource mithilfe des Fragmentierungsfaktors von Spektral-, Zeit- und räumlichen Dimension effizient zuweisen und neu zuordnen. Darüber hinaus wird die Rolle des maschinellen Lernens (ML) für eine verbesserte Bereitstellung der optischen Ressourcen untersucht und das ML basierte Verfahren mit der statischen Ressourcenzuweisung verglichen. Dabei werden zwei Anwendungsbeispiele vorgestellt und analysiert: der Umgang mit einer zeitveränderlichen Verkehrslast in optischen Rechenzentrumsnetzen, und eine Verringerung des Energieverbrauchs und die Zuweisung des Spektrums proportional zu Verkehrsklassen in kombinierten Glasfaser-Funknetzwerken

Applications of perfect difference codes in fiber-optics and wireless optical code-division multiplexing/multiple-access systems

After establishing itself in the radio domain, Spread spectrum code-division multiplexing/multiple-access (CDMA) has seen a recent upsurge in optical domain as well. Due to its fairness, flexibility, service differentiation and increased inherent security, CDMA is proved to be more suitable for the bursty nature of local area networks than synchronous multiplexing techniques like Frequency/Wavelength Division Multiplexing (F/WDM) and Time Division Multiplexing (TDM). In optical domain, CDMA techniques are commonly known as Optical-CDMA (O-CDMA). All optical CDMA systems are plagued with the problem of multiple-access interference (MAI). Spectral amplitude coding (SAC) is one of the techniques used in the literature to deal with the problem of MAI. The choice of spreading code in any CDMA system is another way to ensure the successful recovery of data at the receiving end by minimizing the effect of MAI and it also dictates the hardware design of the encoder and decoder. This thesis focuses on the efficient design of encoding and decoding hardware. Perfect difference codes (PDC) are chosen as spreading sequences due to their good correlation properties. In most of the literature, evaluation of error probability is based on the assumptions of ideal conditions. Such assumptions ignore major physical impairments such as power splitting losses at the multiplexers of transmitters and receivers, and gain losses at the receivers, which may in practice be an overestimate or underestimate of the actual probability of error. This thesis aims to investigate thoroughly with the consideration of practical impairments the applications of PDCs and other spreading sequences in optical communications systems based on spectral-amplitude coding and utilizing codedivision as multiplexing/multiple-access technique. This work begins with a xix general review of optical CDMA systems. An open-ended practical approach has been used to evaluate the actual error probabilities of OCDM/A systems under study. It has been concluded from results that mismatches in the gains of photodetectors, namely avalanche photodiode (APDs), used at the receiver side and uniformity loss in the optical splitters results in the inaccurate calculation of threshold level used to detect the data and can seriously degrade the system bit error rate (BER) performance. This variation in the threshold level can be compensated by employing techniques which maintain a constant interference level so that the decoding architecture does not have to estimate MAI every time to make a data bit decision or by the use of balanced sequences. In this thesis, as a solution to the above problem, a novel encoding and decoding architecture is presented for perfect difference codes based on common zero code technique which maintains a constant interference level at all instants in CDM system and thus relieves the need of estimating interference. The proposed architecture only uses single multiplexer at the transmitters for all users in the system and a simple correlation based receiver for each user. The proposed configuration not only preserves the ability of MAI in Spectral-Amplitude Coding SAC-OCDM system, but also results in a low cost system with reduced complexity. The results show that by using PDCs in such system, the influence of MAI caused by other users can be reduced, and the number of active users can be increased significantly. Also a family of novel spreading sequences are constructed called Manchestercoded Modified Legendre codes (MCMLCs) suitable for SAC based OCDM systems. MCMLCs are designed to be used for both single-rate and Multirate systems. First the construction of MCMLCs is presented and then the bit error rate performance is analyzed. Finally the proposed encoding/decoding architecture utilizing perfect difference codes is applied in wireless infrared environment and the performance is found to be superior to other codes

Optical flow switched networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 253-279).In the four decades since optical fiber was introduced as a communications medium, optical networking has revolutionized the telecommunications landscape. It has enabled the Internet as we know it today, and is central to the realization of Network-Centric Warfare in the defense world. Sustained exponential growth in communications bandwidth demand, however, is requiring that the nexus of innovation in optical networking continue, in order to ensure cost-effective communications in the future. In this thesis, we present Optical Flow Switching (OFS) as a key enabler of scalable future optical networks. The general idea behind OFS-agile, end-to-end, all-optical connections-is decades old, if not as old as the field of optical networking itself. However, owing to the absence of an application for it, OFS remained an underdeveloped idea-bereft of how it could be implemented, how well it would perform, and how much it would cost relative to other architectures. The contributions of this thesis are in providing partial answers to these three broad questions. With respect to implementation, we address the physical layer design of OFS in the metro-area and access, and develop sensible scheduling algorithms for OFS communication. Our performance study comprises a comparative capacity analysis for the wide-area, as well as an analytical approximation of the throughput-delay tradeoff offered by OFS for inter-MAN communication. Lastly, with regard to the economics of OFS, we employ an approximate capital expenditure model, which enables a throughput-cost comparison of OFS with other prominent candidate architectures. Our conclusions point to the fact that OFS offers significant advantage over other architectures in economic scalability.(cont.) In particular, for sufficiently heavy traffic, OFS handles large transactions at far lower cost than other optical network architectures. In light of the increasing importance of large transactions in both commercial and defense networks, we conclude that OFS may be crucial to the future viability of optical networking.by Guy E. Weichenberg.Ph.D

Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

Journal of Telecommunications and Information Technology

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MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

Gaze-Based Human-Robot Interaction by the Brunswick Model

We present a new paradigm for human-robot interaction based on social signal processing, and in particular on the Brunswick model. Originally, the Brunswick model copes with face-to-face dyadic interaction, assuming that the interactants are communicating through a continuous exchange of non verbal social signals, in addition to the spoken messages. Social signals have to be interpreted, thanks to a proper recognition phase that considers visual and audio information. The Brunswick model allows to quantitatively evaluate the quality of the interaction using statistical tools which measure how effective is the recognition phase. In this paper we cast this theory when one of the interactants is a robot; in this case, the recognition phase performed by the robot and the human have to be revised w.r.t. the original model. The model is applied to Berrick, a recent open-source low-cost robotic head platform, where the gazing is the social signal to be considered

Journal of Telecommunications and Information Technology, 2003, nr 3

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