Traffic and performance evaluation for optical networks. An Investigation into Modelling and Characterisation of Traffic Flows and Performance Analysis and Engineering for Optical Network Architectures.

The convergence of multiservice heterogeneous networks and ever increasing Internet applications, like peer to peer networking and the increased number of users and services, demand a more efficient bandwidth allocation in optical networks. In this context, new architectures and protocols are needed in conjuction with cost effective quantitative methodologies in order to provide an insight into the performance aspects of the next and future generation Internets. This thesis reports an investigation, based on efficient simulation methodologies, in order to assess existing high performance algorithms and to propose new ones. The analysis of the traffic characteristics of an OC-192 link (9953.28 Mbps) is initially conducted, a requirement due to the discovery of self-similar long-range dependent properties in network traffic, and the suitability of the GE distribution for modelling interarrival times of bursty traffic in short time scales is presented. Consequently, using a heuristic approach, the self-similar properties of the GE/G/¿ are being presented, providing a method to generate self-similar traffic that takes into consideration burstiness in small time scales. A description of the state of the art in optical networking providing a deeper insight into the current technologies, protocols and architectures in the field, which creates the motivation for more research into the promising switching technique of ¿Optical Burst Switching¿ (OBS). An investigation into the performance impact of various burst assembly strategies on an OBS edge node¿s mean buffer length is conducted. Realistic traffic characteristics are considered based on the analysis of the OC-192 backbone traffic traces. In addition the effect of burstiness in the small time scales on mean assembly time and burst size distribution is investigated. A new Dynamic OBS Offset Allocation Protocol is devised and favourable comparisons are carried out between the proposed OBS protocol and the Just Enough Time (JET) protocol, in terms of mean queue length, blocking and throughput. Finally the research focuses on simulation methodologies employed throughout the thesis using the Graphics Processing Unit (GPU) on a commercial NVidia GeForce 8800 GTX, which was initially designed for gaming computers. Parallel generators of Optical Bursts are implemented and simulated in ¿Compute Unified Device Architecture¿ (CUDA) and compared with simulations run on general-purpose CPU proving the GPU to be a cost-effective platform which can significantly speed-up calculations in order to make simulations of more complex and demanding networks easier to develop

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Modulation and Multiple Access Techniques for Ultra-Wideband Communication Systems

Two new energy detection (ED) Ultra-Wideband (UWB) systems are proposed in this dissertation. The first one is an ED UWB system based on pulse width modulation (PWM). The bit error rate (BER) performance of this ED PWM system is slightly worse than ED pulse position modulation (PPM) system in additive white Gaussian noise (AWGN) channels. However, the BER performance of this ED PWM system surpasses that of a PPM system in multipath channels since a PWM system does not suffer cross-modulation interference (CMI) as a PPM system. In the presence of synchronization errors, the BER performance of a PWM system also surpasses that of a PPM system. The second proposed ED UWB system is based on using two pulses, which are the different-order derivatives of the Gaussian pulse, to transmitted bit 0 or 1. These pulses are appropriately chosen to separate their spectra in frequency domain.The receiver is composed of two energy detection branches and each branch has a filter which captures the signal energy of either bit 0 or 1. The outputs of two branches are subtracted from each other to generate the decision statistic and the value of this statistic is compared to a threshold to determine the transmitted bits. This system is named as acf{GFSK} system in this dissertation and it exhibits the same BER performance as a PPM system in AWGN channels. In multipath channels, a GFSK system surpasses a PPM system because it does not suffer CMI. And the BER performance of a GFSK system is better than a PPM system in the presence of synchronization errors. When a GFSK system is compared to a PWM system, it will always achieve approximately 2 dB improvement in AWGN channels, multipath channels, and in the presence synchronization errors. However, a PWM system uses lower-order derivatives of the Gaussian pulse to transmit signal, and this leads to a simple pulse generator. In this dissertation, an optimal threshold is applied to improve PPM system performance. The research results show that the application of an optimal threshold can e

Modulation and Multiple Access Techniques for Ultra-Wideband Communication Systems

Two new energy detection (ED) Ultra-Wideband (UWB) systems are proposed in this dissertation. The first one is an ED UWB system based on pulse width modulation (PWM). The bit error rate (BER) performance of this ED PWM system is slightly worse than ED pulse position modulation (PPM) system in additive white Gaussian noise (AWGN) channels. However, the BER performance of this ED PWM system surpasses that of a PPM system in multipath channels since a PWM system does not suffer cross-modulation interference (CMI) as a PPM system. In the presence of synchronization errors, the BER performance of a PWM system also surpasses that of a PPM system. The second proposed ED UWB system is based on using two pulses, which are the different-order derivatives of the Gaussian pulse, to transmitted bit 0 or 1. These pulses are appropriately chosen to separate their spectra in frequency domain.The receiver is composed of two energy detection branches and each branch has a filter which captures the signal energy of either bit 0 or 1. The outputs of two branches are subtracted from each other to generate the decision statistic and the value of this statistic is compared to a threshold to determine the transmitted bits. This system is named as acf{GFSK} system in this dissertation and it exhibits the same BER performance as a PPM system in AWGN channels. In multipath channels, a GFSK system surpasses a PPM system because it does not suffer CMI. And the BER performance of a GFSK system is better than a PPM system in the presence of synchronization errors. When a GFSK system is compared to a PWM system, it will always achieve approximately 2 dB improvement in AWGN channels, multipath channels, and in the presence synchronization errors. However, a PWM system uses lower-order derivatives of the Gaussian pulse to transmit signal, and this leads to a simple pulse generator. In this dissertation, an optimal threshold is applied to improve PPM system performance. The research results show that the application of an optimal threshold can e

Modelling of self-similar teletraffic for simulation

Recent studies of real teletraffic data in modern computer networks have shown that teletraffic exhibits self-similar (or fractal) properties over a wide range of time scales. The properties of self-similar teletraffic are very different from the traditional models of teletraffic based on Poisson, Markov-modulated Poisson, and related processes. The use of traditional models in networks characterised by self-similar processes can lead to incorrect conclusions about the performance of analysed networks. These include serious over-estimations of the performance of computer networks, insufficient allocation of communication and data processing resources, and difficulties ensuring the quality of service expected by network users. Thus, full understanding of the self-similar nature in teletraffic is an important issue. Due to the growing complexity of modern telecommunication networks, simulation has become the only feasible paradigm for their performance evaluation. In this thesis, we make some contributions to discrete-event simulation of networks with strongly-dependent, self-similar teletraffic. First, we have evaluated the most commonly used methods for estimating the self-similarity parameter H using appropriately long sequences of data. After assessing properties of available H estimators, we identified the most efficient estimators for practical studies of self-similarity. Next, the generation of arbitrarily long sequences of pseudo-random numbers possessing specific stochastic properties was considered. Various generators of pseudo-random self-similar sequences have been proposed. They differ in computational complexity and accuracy of the self-similar sequences they generate. In this thesis, we propose two new generators of self-similar teletraffic: (i) a generator based on Fractional Gaussian Noise and Daubechies Wavelets (FGN-DW), that is one of the fastest and the most accurate generators so far proposed; and (ii) a generator based on the Successive Random Addition (SRA) algorithm. Our comparative study of sequential and fixed-length self-similar pseudo-random teletraffic generators showed that the FFT, FGN-DW and SRP-FGN generators are the most efficient, both in the sense of accuracy and speed. To conduct simulation studies of telecommunication networks, self-similar processes often need to be transformed into suitable self-similar processes with arbitrary marginal distributions. Thus, the next problem addressed was how well the self-similarity and autocorrelation function of an original self-similar process are preserved when the self-similar sequences are converted into suitable self-similar processes with arbitrary marginal distributions. We also show how pseudo-random self-similar sequences can be applied to produce a model of teletraffic associated with the transmission of VBR JPEG /MPEG video. A combined gamma/Pareto model based on the application of the FGN-DW generator was used to synthesise VBR JPEG /MPEG video traffic. Finally, effects of self-similarity on the behaviour of queueing systems have been investigated. Using M/M/1/∞ as a reference queueing system with no long-range dependence, we have investigated how self-similarity and long-range dependence in arrival processes affect the length of sequential simulations being executed for obtaining steady-state results with the required level of statistical error. Our results show that the finite buffer overflow probability of a queueing system with self-similar input is much greater than the equivalent queueing system with Poisson or a short-range dependent input process, and that the overflow probability increases as the self-similarity parameter approaches one

Quantum macroeconomics theory

The quantum macroeconomics theory is formulated for the first time, assuming that the business cycle has the discrete-time oscillations spectrum in analogy with the electronics excitations discrete-time spectrum in the Bohr’s atom model in the quantum physics. The quantum macroeconomics theory postulates that the discrete-time transitions from one level of GIP((t), GDP(t), GNP(t) to another level of GIP((t), GDP(t), GNP(t) will occur in the nonlinear dynamic economic systems at the time, when: 1) The land, labour and capital resources are added / released to the production/service processes in the form of quanta; 2) The disruptive scientific/technological/financial/social/political innovation is introduced, creating the resonance conditions necessary to amplify/attenuate the value of GIP((t), GDP(t), GNP(t), during the evolution process of the nonlinear dynamic economic system in the time domain. The authors think that the general information product on the time GIP((t), the general domestic product on the time GDP(t), and the general national product on the time GNP(t), are the discrete-time digital signals (the Ledenyov discrete-time digital waves with the Markov information) in distinction from the continuous-time signals (the Kitchin, Juglar, Kuznets, Kondratieff continuous waves), because of the discrete-time nature of the disruptive scientific/technological/financial/social/political innovations. The authors apply the quantum macroeconomics theory to research and develop a new software program for the accurate characterization and forecasting of GIP((t), GDP(t), GNP(t) dependences changes in the economies of scales and scopes in the time domain for the use by the central / commercial banks

Journal of Telecommunications and Information Technology, 2011, nr 2

kwartalni

Quantum macroeconomics theory

The quantum macroeconomics theory is formulated for the first time, assuming that the business cycle has the discrete-time oscillations spectrum in analogy with the electronics excitations discrete-time spectrum in the Bohr’s atom model in the quantum physics. The quantum macroeconomics theory postulates that the discrete-time transitions from one level of GIP((t), GDP(t), GNP(t) to another level of GIP((t), GDP(t), GNP(t) will occur in the nonlinear dynamic economic systems at the time, when: 1) The land, labour and capital resources are added / released to the production/service processes in the form of quanta; 2) The disruptive scientific/technological/financial/social/political innovation is introduced, creating the resonance conditions necessary to amplify/attenuate the value of GIP((t), GDP(t), GNP(t), during the evolution process of the nonlinear dynamic economic system in the time domain. The authors think that the general information product on the time GIP((t), the general domestic product on the time GDP(t), and the general national product on the time GNP(t), are the discrete-time digital signals (the Ledenyov discrete-time digital waves with the Markov information) in distinction from the continuous-time signals (the Kitchin, Juglar, Kuznets, Kondratieff continuous waves), because of the discrete-time nature of the disruptive scientific/technological/financial/social/political innovations. The authors apply the quantum macroeconomics theory to research and develop a new software program for the accurate characterization and forecasting of GIP((t), GDP(t), GNP(t) dependences changes in the economies of scales and scopes in the time domain for the use by the central / commercial banks

Quantum macroeconomics theory

The quantum macroeconomics theory is formulated for the first time, assuming that the business cycle has the discrete-time oscillations spectrum in analogy with the electronics excitations discrete-time spectrum in the Bohr’s atom model in the quantum physics. The quantum macroeconomics theory postulates that the discrete-time transitions from one level of GIP((t), GDP(t), GNP(t) to another level of GIP((t), GDP(t), GNP(t) will occur in the nonlinear dynamic economic systems at the time, when: 1) The land, labour and capital resources are added / released to the production/service processes in the form of quanta; 2) The disruptive scientific/technological/financial/social/political innovation is introduced, creating the resonance conditions necessary to amplify/attenuate the value of GIP((t), GDP(t), GNP(t), during the evolution process of the nonlinear dynamic economic system in the time domain. The authors think that the general information product on the time GIP((t), the general domestic product on the time GDP(t), and the general national product on the time GNP(t), are the discrete-time digital signals (the Ledenyov discrete-time digital waves with the Markov information) in distinction from the continuous-time signals (the Kitchin, Juglar, Kuznets, Kondratieff continuous waves), because of the discrete-time nature of the disruptive scientific/technological/financial/social/political innovations. The authors apply the quantum macroeconomics theory to research and develop a new software program for the accurate characterization and forecasting of GIP((t), GDP(t), GNP(t) dependences changes in the economies of scales and scopes in the time domain for the use by the central / commercial banks