Performance Modeling and Analysis of Wireless Local Area Networks with Bursty Traffic

The explosive increase in the use of mobile digital devices has posed great challenges in the design and implementation of Wireless Local Area Networks (WLANs). Ever-increasing demands for high-speed and ubiquitous digital communication have made WLANs an essential feature of everyday life. With audio and video forming the highest percentage of traffic generated by multimedia applications, a huge demand is placed for high speed WLANs that provide high Quality-of-Service (QoS) and can satisfy end user’s needs at a relatively low cost. Providing video and audio contents to end users at a satisfactory level with various channel quality and current battery capacities requires thorough studies on the properties of such traffic. In this regard, Medium Access Control (MAC) protocol of the 802.11 standard plays a vital role in the management and coordination of shared channel access and data transmission. Therefore, this research focuses on developing new efficient analytical models that evaluate the performance of WLANs and the MAC protocol in the presence of bursty, correlated and heterogeneous multimedia traffic using Batch Markovian Arrival Process (BMAP). BMAP can model the correlation between different packet size distributions and traffic rates while accurately modelling aggregated traffic which often possesses negative statistical properties. The research starts with developing an accurate traffic generator using BMAP to capture the existing correlations in multimedia traffics. For validation, the developed traffic generator is used as an arrival process to a queueing model and is analyzed based on average queue length and mean waiting time. The performance of BMAP/M/1 queue is studied under various number of states and maximum batch sizes of BMAP. The results clearly indicate that any increase in the number of states of the underlying Markov Chain of BMAP or maximum batch size, lead to higher burstiness and correlation of the arrival process, prompting the speed of the queue towards saturation. The developed traffic generator is then used to model traffic sources in IEEE 802.11 WLANs, measuring important QoS metrics of throughput, end-to-end delay, frame loss probability and energy consumption. Performance comparisons are conducted on WLANs under the influence of multimedia traffics modelled as BMAP, Markov Modulated Poisson Process and Poisson Process. The results clearly indicate that bursty traffics generated by BMAP demote network performance faster than other traffic sources under moderate to high loads. The model is also used to study WLANs with unsaturated, heterogeneous and bursty traffic sources. The effects of traffic load and network size on the performance of WLANs are investigated to demonstrate the importance of burstiness and heterogeneity of traffic on accurate evaluation of MAC protocol in wireless multimedia networks. The results of the thesis highlight the importance of taking into account the true characteristics of multimedia traffics for accurate evaluation of the MAC protocol in the design and analysis of wireless multimedia networks and technologies

Non-Intrusive Measurement in Packet Networks and its Applications

PhDNetwork measurementis becoming increasingly important as a meanst o assesst he performanceo f packet networks. Network performance can involve different aspects such as availability, link failure detection etc, but in this thesis, we will focus on Quality of Service (QoS). Among the metrics used to define QoS, we are particularly interested in end-to-end delay performance. Recently, the adoption of Service Level Agreements (SLA) between network operators and their customersh as becomea major driving force behind QoS measurementm: easurementi s necessaryt o produce evidence of fulfilment of the requirements specified in the SLA. Many attempts to do QoS based packet level measurement have been based on Active Measurement, in which the properties of the end-to-end path are tested by adding testing packets generated from the sending end. The main drawback of active probing is its intrusive nature which causes extraburden on the network, and has been shown to distort the measured condition of the network. The other category of network measurement is known as Passive Measurement. In contrast to Active Measurement, there are no testing packets injected into the network, therefore no intrusion is caused. The proposed applications using Passive Measurement are currently quite limited. But Passive Measurement may offer the potential for an entirely different perspective compared with Active Measurements In this thesis, the objective is to develop a measurement methodology for the end-to-end delay performance based on Passive Measurement. We assume that the nodes in a network domain are accessible.F or example, a network domain operatedb y a single network operator. The novel idea is to estimate the local per-hop delay distribution based on a hybrid approach (model and measurement-based)W. ith this approach,t he storagem easurementd ata requirement can be greatly alleviated and the overhead put in each local node can be minimized, so maintaining the fast switching operation in a local switcher or router. Per-hop delay distributions have been widely used to infer QoS at a single local node. However, the end-to-end delay distribution is more appropriate when quantifying delays across an end-to-end path. Our approach is to capture every local node's delay distribution, and then the end-to-end delay distribution can be obtained by convolving the estimated delay distributions. In this thesis, our algorithm is examined by comparing the proximity of the actual end-to-end delay distribution with the estimated one obtained by our measurement method under various conditions. e. g. in the presence of Markovian or Power-law traffic. Furthermore, the comparison between Active Measurement and our scheme is also studied. 2 Network operators may find our scheme useful when measuring the end-to-end delay performance. As stated earlier, our scheme has no intrusive effect. Furthermore, the measurement result in the local node can be re-usable to deduce other paths' end-to-end delay behaviour as long as this local node is included in the path. Thus our scheme is more scalable compared with active probing

Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

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

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

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

Analyse mathématique, méthode de calcul de la gigue et applications aux réseaux Internet

RÉSUMÉ Internet, ces dernières années, sert de support de communication à un grand nombre d’applications. L’évolution des réseaux à haut débit ont facilité le progrès des applications multimédia comme la voix sur IP, la vidéo streaming ou la vidéo interactive en temps réel... La variation de la disponibilité des ressources du réseau ne peut pas garantir une bonne qualité à tout moment pour ces services. C’est dans ce contexte que les travaux de ce projet de doctorat s’inscrivent et précisément dans le cadre de l’optimisation de la qualité de service (QoS). Les mécanismes de contrôle de QoS sont variés. On retrouve le contrôle de délai, assuré par la stratégie d’ordonnancement des paquets. Le contrôle de débit, quant à lui, fait en sorte que le débit de la source soit égal à la bande passante disponible dans le réseau. Excepté que les applications vidéo, surtout en temps réel, sont très sensibles à la variation du délai, appelée la gigue. En effet, la qualité perçue par les clients des vidéos en ligne dépend étroitement de la gigue. Une augmentation de la gigue engendre principalement des problèmes de démarrage retardé de la vidéo, des interruptions au cours de la vidéo et des distorsions de la résolution. L’objectif de cette thèse est d’étudier le paramètre de la gigue, qui demeure peu étudiée dans la littérature sur les réseaux IP, ainsi que d’envisager l’impact de l’augmentation de ce paramètre sur la vidéo transmise sur IP, l’une des applications les plus populaires de nos jours. Toutefois, au-delà des difficultés de la modélisation du trafic et du réseau, cet objectif majeur pose de nombreuses problématiques. Comment calculer la gigue analytiquement pour un trafic modélisé par des distributions généralisées au niveau paquet ? Est-ce que les modèles proposés sont suffisamment simples et faciles à calculer ? Comment intégrer ces nouvelles formalisations pour le contrôle des performances ? Comment l’estimation analytique peut- elle minimiser le trafic des paquets de contrôle des connexions vidéo? Nous explorons tout d’abord le calcul de la gigue dans des files d’attente avec des trafics autres que le trafic Poisson. Ce dernier est largement utilisé pour modéliser le trafic sur Internet étant donnée sa simplicité en échange de la imprécision. L’idée pour le calcul de la gigue est d’utiliser, d’une part la même formule que le cas du Poisson mais en intégrant d’autres distributions, et d’autre part des approximations et des hypothèses quand la caractérisation analytique du temps de transit n’est pas possible. Nous adoptons la simulation pour valider les modèles approximatifs. L’ensemble de simulations montre que la gigue moyenne calculée par notre modèle et celle obtenue par simulation coïncident avec des intervalles de confiance adéquats. De plus, le temps de calcul estimé pour évaluer la gigue est minime, ce qui facilite l’utilisation des formules proposées dans des outils de contrôle et en optimisation.-----------ABSTRACT In recent years, we have witnessed the huge use of the Internet Protocol for delivering multimedia trafic. Developments in broadband networks led the progress in multimedia applications such as voice over IP, video streaming or real-time videos. However, the stochastic nature of the networks, in particular mobile networks, make it difficult to maintain a good quality at all times. The research of this PhD thesis deals with the improvement of the quality of service (QoS) for this kind of applications. Current network protocols provide multiple QoS control mechanism. Congestion control and transmission delay optimization are provided by packet scheduling strategies and bandwidth planning. Moreover, flow control adjusts the mismatch between the video server rate and the receiver available bandwidth. Nevertheless, video applications, in particular interactive videos, are very sensitive to delay variation, commonly called jitter. Indeed, the customers’ perceived video quality depends on it. A jitter increase may cause a large video start-up delay, video interruptions and a decrease of image quality. The main objective of this thesis is the study of jitter, which is not much studied in the IP literature. We also examine the impact of the increase of this parameter on video transmission. However, beyond the difficulties of modeling traffic and network, this major objective raises many other issues. How to calculate jitter analytically for traffic models with general distributions? Are the proposed models sufficiently simple and easy to calculate? How to integrate these new formalizations into performance monitoring? How can the analytical estimate minimize the traffic control packets exchange for each video connection? We first explore the jitter calculation in queues with traffic other than Poisson traffic, that was widely used to model Internet traffic because of its simplicity. The idea is to compute jitter with the same formula for the Poisson traffic case, but with other distributions. For this, we need some approximations and assumptions when the analytical characterization of the transit time is not possible. We adopt simulations to validate the approximate models. The set of simulations shows that the average jitter calculated by our model and by simulation coincide within an appropriate confidence intervals. Moreover, the execution time to evaluate jitter is small, which facilitates the use of the proposed formulas in control tools and in optimization models. We then study the possibility of exploiting this analytical results to control jitter buffers, an important component in the video transmission. We find that it is possible to evaluate its performances analytically by estimating jitter inside this type of buffer

Journal of Telecommunications and Information Technology, 2002, nr 3

kwartalni