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

Video traffic modeling and delivery

Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

Quality aspects of Internet telephony

Internet telephony has had a tremendous impact on how people communicate. Many now maintain contact using some form of Internet telephony. Therefore the motivation for this work has been to address the quality aspects of real-world Internet telephony for both fixed and wireless telecommunication. The focus has been on the quality aspects of voice communication, since poor quality leads often to user dissatisfaction. The scope of the work has been broad in order to address the main factors within IP-based voice communication. The first four chapters of this dissertation constitute the background material. The first chapter outlines where Internet telephony is deployed today. It also motivates the topics and techniques used in this research. The second chapter provides the background on Internet telephony including signalling, speech coding and voice Internetworking. The third chapter focuses solely on quality measures for packetised voice systems and finally the fourth chapter is devoted to the history of voice research. The appendix of this dissertation constitutes the research contributions. It includes an examination of the access network, focusing on how calls are multiplexed in wired and wireless systems. Subsequently in the wireless case, we consider how to handover calls from 802.11 networks to the cellular infrastructure. We then consider the Internet backbone where most of our work is devoted to measurements specifically for Internet telephony. The applications of these measurements have been estimating telephony arrival processes, measuring call quality, and quantifying the trend in Internet telephony quality over several years. We also consider the end systems, since they are responsible for reconstructing a voice stream given loss and delay constraints. Finally we estimate voice quality using the ITU proposal PESQ and the packet loss process. The main contribution of this work is a systematic examination of Internet telephony. We describe several methods to enable adaptable solutions for maintaining consistent voice quality. We have also found that relatively small technical changes can lead to substantial user quality improvements. A second contribution of this work is a suite of software tools designed to ascertain voice quality in IP networks. Some of these tools are in use within commercial systems today

Buffer management and cell switching management in wireless packet communications

The buffer management and the cell switching (e.g., packet handoff) management using buffer management scheme are studied in Wireless Packet Communications. First, a throughput improvement method for multi-class services is proposed in Wireless Packet System. Efficient traffic management schemes should be developed to provide seamless access to the wireless network. Specially, it is proposed to regulate the buffer by the Selective- Delay Push-In (SDPI) scheme, which is applicable to scheduling delay-tolerant non-real time traffic and delay-sensitive real time traffic. Simulation results show that the performance observed by real time traffics are improved as compared to existing buffer priority scheme in term of packet loss probability. Second, the performance of the proposed SDPI scheme is analyzed in a single CBR server. The arrival process is derived from the superposition of two types of traffics, each in turn results from the superposition of homogeneous ON-OFF sources that can be approximated by means of a two-state Markov Modulated Poisson Process (MMPP). The buffer mechanism enables the ATM layer to adapt the quality of the cell transfer to the QoS requirements and to improve the utilization of network resources. This is achieved by selective-delaying and pushing-in cells according to the class they belong to. Analytical expressions for various performance parameters and numerical results are obtained. Simulation results in term of cell loss probability conform with our numerical analysis. Finally, a novel cell-switching scheme based on TDMA protocol is proposed to support QoS guarantee for the downlink. The new packets and handoff packets for each type of traffic are defined and a new cutoff prioritization scheme is devised at the buffer of the base station. A procedure to find the optimal thresholds satisfying the QoS requirements is presented. Using the ON-OFF approximation for aggregate traffic, the packet loss probability and the average packet delay are computed. The performance of the proposed scheme is evaluated by simulation and numerical analysis in terms of packet loss probability and average packet delay

Leading Modes of the 3pi0 production in proton-proton collisions at incident proton momentum 3.35GeV/c

This work deals with the prompt pp-->pp3pi0 reaction where the 3pi0 do not origin from the decay of narrow resonances like \eta(547), \omega(782), \eta'(958). The reaction was measured for the proton beam momentum of 3.35GeV/c with the WASA-at-COSY detector setup. The dynamics of the reaction is investigated by Dalitz and Nyborg plots studies. The reaction is described by the model assuming simultaneous excitation of two baryon resonances \Delta(1232) and N*(1440) where resonances are identified by their unique decays topology on the missing mass of two protons MMpp dependent Dalitz and Nyborg plots. The ratio R=\Gamma(N*(1440)->N\pi\pi)/\Gamma(N*(1440)->\Delta(1232)\pi->N\pi\pi)= 0.039 +- 0.011(stat.) +- 0.008(sys.) is measured for the first time in a direct way. It shows that the {N*(1440)->\Delta(1232)\pi->N\pi\pi} decay is a leading mode of 3pi0 production. It is also shown that the MMpp is very sensitive to the structure of the spectral line shape of the N*(1440) resonance as well as on the interaction between the \Delta(1232) and N*(1440) resonances. The multipion spectroscopy - a precision tool to directly access the properties of baryon resonances is considered. The pp-->pp\eta(3pi0) reaction was also measured simultaneously. It is shown that the {\eta} production mechanism via N*(1535) is 43.4 +- 0.8(stat.) +- 2.0(sys.) of the total production, for the {\eta} momentum in the CM system q_\eta^CM=0.45-0.7GeV/c. First time momentum dependence of the {\eta} angular distribution is seen, the strongest effect is observed for the cos(\theta_\eta^CM) distribution.Comment: PhD Thesis prepared at the Nuclear Physics Department of the Jagiellonian University, Cracow, Poland, 201

Packet level measurement over wireless access

PhDPerformance Measurement of the IP packet networks mainly comprise of monitoring the network performance in terms of packet losses and delays. If used appropriately, these network parameters (i.e. delay, loss and bandwidth etc) can indicate the performance status of the network and they can be used in fault and performance monitoring, network provisioning, and traffic engineering. Globally, there is a growing need for accurate network measurement to support the commercial use of IP networks. In wireless networks, transmission losses and communication delays strongly affect the performance of the network. Compared to wired networks, wireless networks experience higher levels of data dropouts, and corruption due to issues of channel fading, noise, interference and mobility. Performance monitoring is a vital element in the commercial future of broadband packet networking and the ability to guarantee quality of service in such networks is implicit in Service Level Agreements. Active measurements are performed by injecting probes, and this is widely used to determine the end to end performance. End to end delay in wired networks has been extensively investigated, and in this thesis we report on the accuracy achieved by probing for end to end delay over a wireless scenario. We have compared two probing techniques i.e. Periodic and Poisson probing, and estimated the absolute error for both. The simulations have been performed for single hop and multi- hop wireless networks. In addition to end to end latency, Active measurements have also been performed for packet loss rate. The simulation based analysis has been tried under different traffic scenarios using Poisson Traffic Models. We have sampled the user traffic using Periodic probing at different rates for single hop and multiple hop wireless scenarios. 5 Active probing becomes critical at higher values of load forcing the network to saturation much earlier. We have evaluated the impact of monitoring overheads on the user traffic, and show that even small amount of probing overhead in a wireless medium can cause large degradation in network performance. Although probing at high rate provides a good estimation of delay distribution of user traffic with large variance yet there is a critical tradeoff between the accuracy of measurement and the packet probing overhead. Our results suggest that active probing is highly affected by probe size, rate, pattern, traffic load, and nature of shared medium, available bandwidth and the burstiness of the traffic

Performance analysis of error recovery and congestion control in high-speed networks

In the past few years, Broadband Integrated Services Digital Network (B-ISDN) has received increasing attention as a communication architecture capable of supporting multimedia applications. Among the techniques proposed to implement B-ISDN, Asynchronous Transfer Mode (ATM) is considered to be the most promising transfer technique because of its efficiency and flexibility.In ATM networks, the performance bottleneck of the network, which was once the channel transmission speed, is shifted to the processing speed at the network switching nodes and the propagation delay of the channel. This shift is because the high-speed channel increases the ratio of processing time to packet transmission time and also the ratio of propagation delay to packet transmission time. The increased processing overhead makes it difficult to implement hop-by-hop schemes, which may impose prohibitably high processing at each switching node. The increased propagation delay overhead makes traffic control in ATM a challenge since a large number of packets can be in transit between two ATM switching nodes. Because of these fundamental changes, control schemes developed for traditional networks may not perform efficiently, and thus, new network architectures (congestion control schemes, error control schemes, etc.) are required in ATM networks.In this dissertation, we first present an extensive survey of various traffic control schemes and network protocols for ATM networks. In this survey, possible traffic control schemes are examined, and problems of those schemes and their possible solutions are presented. Next, we investigate two key research issues in ATM networks (and other types of high-speed networks): the effects of protocol-processing overhead and the efficiency of traffic control schemes.We first investigate the effects of protocol-processing overhead on the performance of error recovery schemes. Specifically, we investigate the performance trade-offs between link-by-link and edge-to-edge error recovery schemes. Our results show that for a network with high-speed/low-error-rate channels, an edge-to-edge scheme gives a smaller delay than a link-by-link scheme. We then investigate the effectiveness of a priority packet discarding scheme, a congestion control mechanism suitable for high-speed networks. We derive loss probabilities for each stream and investigate the impact of burstiness of traffic streams on the performance of individual streams

Point Process Models for Heterogeneous Event Time Data

Interaction event times observed on a social network provide valuable information for social scientists to gain insight into complex social dynamics that are challenging to understand. However, it can be difficult to accurately represent the heterogeneity in the data and to model the dependence structure in the network system. This requires flexible models that can capture the complicated dynamics and complex patterns. Point process models offer an elegant framework for modeling event time data. This dissertation concentrates on developing point process models and related diagnostic tools, with a real data application involving an animal behavior network. In this dissertation, we first propose a Markov-modulated Hawkes process (MMHP) model to capture the sporadic and bursty patterns often observed in event time data. A Bayesian inference procedure is developed to evaluate the likelihood by using a variational approximation and the forward-backward algorithm. The validity of the proposed model and associated estimation algorithms is demonstrated using synthetic data and the animal behavior data. Facilitated by the power of the MMHP model, we construct network point process models that can capture a social hierarchy structure by embedding nodes in a latent space that can represent the underlying social ranks. Our model provides a ranking method for social hierarchy studies and describes the dynamics of social hierarchy formation from a novel perspective – taking advantage of the detailed information available in event time data. We show that the network point process models appropriately captures the temporal dynamics and heterogeneity in the network event time data, by providing meaningful inferred rankings and by calibrating the accuracy of predictions with relevant measures of uncertainty. In addition to developing a sensible and flexible model for network event time data, the last part of this dissertation provides essential tools for diagnosing lack of fit issues for such models. We develop a systematic set of diagnostic tools and visualizations for point process models fitted to data in the dynamic network setting. By inspecting the structure of the residual process and Pearson residual on the network, we can validate whether a model adequately captures the temporal and network dependence structures in the observed data