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

The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Partially shared buffers with full or mixed priority

This paper studies a finite-sized discrete-time two-class priority queue. Packets of both classes arrive according to a two-class discrete batch Markovian arrival process (2-DBMAP), taking into account the correlated nature of arrivals in heterogeneous telecommunication networks. The model incorporates time and space priority to provide different types of service to each class. One of both classes receives absolute time priority in order to minimize its delay. Space priority is implemented by the partial buffer sharing acceptance policy and can be provided to the class receiving time priority or to the other class. This choice gives rise to two different queueing models and this paper analyses both these models in a unified manner. Furthermore, the buffer finiteness and the use of space priority raise some issues on the order of arrivals in a slot. This paper does not assume that all arrivals from one class enter the queue before those of the other class. Instead, a string representation for sequences of arriving packets and a probability measure on the set of such strings are introduced. This naturally gives rise to the notion of intra-slot space priority. Performance of these queueing systems is then determined using matrix-analytic techniques. The numerical examples explore the range of service differentiation covered by both models

On the nature and impact of self-similarity in real-time systems

In real-time systems with highly variable task execution times simplistic task models are insufficient to accurately model and to analyze the system. Variability can be tackled using distributions rather than a single value, but the proper charac- terization depends on the degree of variability. Self-similarity is one of the deep- est kinds of variability. It characterizes the fact that a workload is not only highly variable, but it is also bursty on many time-scales. This paper identifies in which situations this source of indeterminism can appear in a real-time system: the com- bination of variability in task inter-arrival times and execution times. Although self- similarity is not a claim for all systems with variable execution times, it is not unusual in some applications with real-time requirements, like video processing, networking and gaming. The paper shows how to properly model and to analyze self-similar task sets and how improper modeling can mask deadline misses. The paper derives an analyti- cal expression for the dependence of the deadline miss ratio on the degree of self- similarity and proofs its negative impact on real-time systems performance through system¿s modeling and simulation. This study about the nature and impact of self- similarity on soft real-time systems can help to reduce its effects, to choose the proper scheduling policies, and to avoid its causes at system design time.This work was developed under a grant from the European Union (FRESCOR-FP6/2005/IST/5-03402).Enrique Hernández-Orallo; Vila Carbó, JA. (2012). On the nature and impact of self-similarity in real-time systems. Real-Time Systems. 48(3):294-319. doi:10.1007/s11241-012-9146-0S294319483Abdelzaher TF, Sharma V, Lu C (2004) A utilization bound for aperiodic tasks and priority driven scheduling. IEEE Trans Comput 53(3):334–350Abeni L, Buttazzo G (1999) QoS guarantee using probabilistic deadlines. 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In: Proc of the 23rd IEEE real-time systems symposium, pp 289–300Erramilli A, Narayan O, Willinger W (1996) Experimental queueing analysis with long-range dependent packet traffic. IEEE/ACM Trans Netw 4(2):209–223Erramilli A, Roughan M, Veitch D, Willinger W (2002) Self-similar traffic and network dynamics. Proc IEEE 90(5):800–819Gardner M (1999) Probabilistic analysis and scheduling of critical soft real-time systems. Phd thesis, University of Illinois, Urbana-ChampaignGarrett MW, Willinger W (1994) Analysis, modeling and generation of self-similar vbr video traffic. In: ACM SIGCOMMHarchol-Balter M (2002) Task assignment with unknown duration. J ACM 49(2):260–288Harchol-Balter M (2007) Foreword: Special issue on new perspective in scheduling. SIGMETRICS Perform Eval Rev 34(4):2–3Harchol-Balter M, Downey AB (1997) Exploiting process lifetime distributions for dynamic load balancing. ACM Trans Comput Syst 15(3):253–285Hernandez-Orallo E, Vila-Carbo J (2007) Network performance analysis based on histogram workload models. In: Proceedings of the 15th international symposium on modeling, analysis, and simulation of computer and telecommunication systems (MASCOTS), pp 331–336Hernandez-Orallo E, Vila-Carbo J (2010) Analysis of self-similar workload on real-time systems. In: IEEE real-time and embedded technology and applications symposium (RTAS). IEEE Computer Society, Washington, pp 343–352Hernández-Orallo E, Vila-Carbó J (2010) Network queue and loss analysis using histogram-based traffic models. Comput Commun 33(2):190–201Hughes CJ, Kaul P, Adve SV, Jain R, Park C, Srinivasan J (2001) Variability in the execution of multimedia applications and implications for architecture. SIGARCH Comput Archit News 29(2):254–265Leland W, Ott TJ (1986) Load-balancing heuristics and process behavior. 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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

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig