Thesis (Ph. D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2004. / "A dissertation in engineering and computer networking." Advisor: Ghulam Chaudhry. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed Feb. 22, 2006. Includes bibliographical references (leaves 135-157). Online version of the print edition.

ZigBee is a substandard of IEEE 802.15 family that is specially designed to take care of factors such as power, data rate and area that primarily affect network performance. This has controlling and monitoring capability, which finds potential applications in different sectors. ZigBee allows the concept of hybrid networks and mobility. A comprehensive analysis of ZigBee networks was carried out by constructing and simulating the networks to evaluate the performance in terms of throughput, delay, network load, and packets dropped. This research is aimed at evaluating the effect of network topology on the system performance. A careful review of simulation platforms brought the conclusion of using OPNET Modeler which has the required frame work. Different network topologies of simple and hybrid were built and simulated. Throughout the simulations, the best-case scenarios were drawn to the conclusion by the graphical analysis of parameters of evaluation. Mobile networks were constructed and simulated to investigate the effect of mobility on communication.

The Transmission Control Protocol (TCP) is one of the core protocols of the Internet protocol suite. In the wired network, TCP performs remarkably well due to its scalability and distributed end-to-end congestion control algorithms. However, many studies have shown that the unmodified standard TCP performs poorly in networks with large bandwidth-delay products and/or lossy wireless links. In this thesis, we analyze the problems TCP exhibits in the wireless communication and develop TCP congestion control algorithm for mobile applications. We show that the optimal TCP congestion control and link scheduling scheme amounts to window-control oriented implicit primaldual solvers for underlying network utility maximization. Based on this idea, we used a scalable congestion control algorithm called QUeueIng-Control (QUIC) TCP where it utilizes queueing-delay based MaxWeight-type scheduler for wireless links developed in [34]. Simulation and test results are provided to evaluate the proposed schemes in practical networks. / by Gee Won Han. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

In recent years, global mobile data traffic has been increasing exponentially as mobile devices pervade our daily lives. To cope with the ever growing demands for higher data rates and seamless connectivity, one solution is to drastically increase the number of macro base stations in the conventional cellular architecture. However, this results in high deployment costs. Deploying low-power nodes such as relays that do not require a wired backhaul connection within a macrocell is one of cost-effective ways to extend high data rate coverage range. Relays are typically deployed to increase signal strength in poor coverage areas or to eliminate dead spots. But more importantly, relays provide a natural diversity, called cooperative diversity. In addition to a direct signal from a base station, extra copies of the same signal are forwarded from relays. Utilizing this diversity at the destination can yield significant performance enhancements. Thus, cooperative relay strategies need to be considered to enable high data rate coverage in a cost-effective manner. In this dissertation, we consider a simple single-relay network and present low-complexity and power-efficient cooperative relay designs that can achieve low error rate. We first study decode-and-forward (DF) relay networks with a single antenna at each node, where the relay decodes the received signal and forwards the re-encoded information to the destination. In DF relay scheme, decoding at the relay is not perfect and the error-propagation phenomenon is a detrimental problem, preventing the destination from collecting the cooperative diversity. To enable cooperative diversity in DF relay networks, we adopt link-adaptive power-scaling relay strategies where the relay scales the transmission power of the re-encoded signal based on the reliability of the source-relay link. We generalize power-profile designs and analyze the diversity order enabled by the general power-profile designs. We provide necessary and sufficient conditions for the designs to enable full cooperative diversity at the destination. In the second part of this dissertation, we extend the power-scaling relay strategy to DF multi-input multi-output (MIMO) relay networks, where multiple antennas are adopted at each node, and show that full cooperative diversity can also be achieved here. To collect spatial diversity provided by multiple antennas without using maximum-likelihood equalizers (MLEs) or near-ML detectors which exhibit high complexity, channel-controlled automatic repeat request (CC-ARQ) scheme is developed for DF MIMO relay networks to enable spatial diversity with linear equalizers (LEs) maintaining low-complexity. We also show that joint cooperative and spatial diversity can be achieved at the destination when the power-scaling strategy and the CC-ARQ with LEs are combined. Finally, amplify-and-forward (AF) MIMO relay designs, where the relay simply amplifies the received signal and forwards it to the destination, are studied with consideration of peak-power constraints at the relay. One practical concern for AF relaying is that the output signal at the relay may suffer from large peak-to-average power ratio (PAR), which may cause nonlinear distortion and/or saturation in the transmitted signal due to the limited linear range of power amplifiers. Thus, we first investigate peak-power constrained power-scaling strategies and find a sufficient condition to enable joint cooperative and spatial diversity at the destination. Based on this study, we propose simple and practical AF MIMO relay designs with peak-power constraint at the relay. CC-ARQ is also applied to AF MIMO relay networks to reduce the decoding complexity.

NETI@home is an open-source software package that collects network performance statistics from end-systems. It has been written for and tested on the Windows, Solaris, and Linux operating systems, with testing for other operating systems to be completed soon. NETI@home is designed to run on end-user machines and collect various statistics about Internet performance. These statistics are then sent to a server at the Georgia Institute of Technology, where they are collected and made publicly available. This tool gives researchers much needed data on the end-to-end performance of the Internet, as measured by end-users. NETI@homes basic approach is to sniff packets sent from and received by the host and infer performance metrics based on these observed packets. NETI@home users are able to select a privacy level that determines what types of data are gathered, and what is not reported. NETI@home is designed to be an unobtrusive software system that runs quietly in the background with little or no intervention by the user, and using few resources.

With the emergence of computer networks as one of the primary platforms of communication, and with their adoption for an increasingly broad range of applications, there is a growing need for high-quality network traffic measurements to better understand, characterize and engineer the network behaviors. Due to the inherent lack of fine-grained measurement capabilities in the original design of the Internet, it does not have enough data or information to compute or even approximate some traffic statistics such as traffic matrices and per-link delay. While it is possible to infer these statistics from indirect aggregate measurements that are widely supported by network measurement devices (e.g., routers), how to obtain the best possible inferences is often a challenging research problem. We name this as "too little data" problem after its root cause. Interestingly, while "too little data" is clearly a problem, "too much data" is not a blessing either. With the rapid increase of network link speeds, even to keep sampled summarized network traffic (for inferring various network statistics) at low sample rates results in too much data to be stored, processed, and transmitted over measurement devices. In summary high-quality measurements in today's Internet is very challenging due to resource limitations and lack of built-in support, manifested as either "too little data" or "too much data". We present some new practices and proposals to alleviate these two problems.The contribution is four fold: i) designing universal methodologies towards ideal network traffic measurements; ii) providing accurate estimations for several critical traffic statistics guided by the proposed methodologies; iii) offering multiple useful and extensible building blocks which can be used to construct a universal network measurement system in the future; iv) leading to some notable mathematical results such as a new large deviation theorem that finds applications in various areas.

The objective of the proposed research is to design and evaluate end-to-end solutions to support the Quality of Experience (QoE) for the Internet Protocol Television (IPTV) service. IPTV is a system that integrates voice, video, and data delivery into a single Internet Protocol (IP) framework to enable interactive broadcasting services at the subscribers. It promises significant advantages for both service providers and subscribers. For instance, unlike conventional broadcasting systems, IPTV broadcasts will not be restricted by the limited number of channels in the broadcast/radio spectrum. Furthermore, IPTV will provide its subscribers with the opportunity to access and interact with a wide variety of high-quality on-demand video content over the Internet. However, these advantages come at the expense of stricter quality of service (QoS) requirements than traditional Internet applications. Since IPTV is considered as a real-time broadcast service over the Internet, the success of the IPTV service depends on the QoE perceived by the end-users. The characteristics of the video traffic as well as the high-quality requirements of the IPTV broadcast impose strict requirements on transmission delay. IPTV framework has to provide mechanisms to satisfy the stringent delay, jitter, and packet loss requirements of the IPTV service over lossy transmission channels with varying characteristics. The proposed research focuses on error recovery and channel change latency problems in IPTV networks. Our specific aim is to develop a content delivery framework that integrates content features, IPTV application requirements, and network characteristics in such a way that the network resource utilization can be optimized for the given constraints on the user perceived service quality. To achieve the desired QoE levels, the proposed research focuses on the design of resource optimal server-based and peer-assisted delivery techniques. First, by analyzing the tradeoffs on the use of proactive and reactive repair techniques, a solution that optimizes the error recovery overhead is proposed. Further analysis on the proposed solution is performed by also focusing on the use of multicast error recovery techniques. By investigating the tradeoffs on the use of network-assisted and client-based channel change solutions, distributed content delivery frameworks are proposed to optimize the error recovery performance. Next, bandwidth and latency tradeoffs associated with the use of concurrent delivery streams to support the IPTV channel change are analyzed, and the results are used to develop a resource-optimal channel change framework that greatly improves the latency performance in the network. For both problems studied in this research, scalability concerns for the IPTV service are addressed by properly integrating peer-based delivery techniques into server-based solutions.

The heavy-tailed traffic from wireless users, caused by the emerging Internet and multimedia applications, induces extremely dynamic and variable network environment, which can fundamentally change the way in which wireless networks are conceived, designed, and operated. This thesis is concerned with modeling, analysis, and optimization of wireless networks in the presence of heavy tails. First, a novel traffic model is proposed, which captures the inherent relationship between the traffic dynamics and the joint effects of the mobility variability of network users and the spatial correlation in their observed physical phenomenon. Next, the asymptotic delay distribution of wireless users is analyzed under different traffic patterns and spectrum conditions, which reveals the critical conditions under which wireless users can experience heavy-tailed delay with significantly degraded QoS performance. Based on the delay analysis, the fundamental impact of heavy-tailed environment on network stability is studied. Specifically, a new network stability criterion, namely moment stability, is introduced to better characterize the QoS performance in the heavy-tailed environment. Accordingly, a throughput-optimal scheduling algorithm is proposed to maximize network throughput while guaranteeing moment stability. Furthermore, the impact of heavy-tailed spectrum on network connectivity is investigated. Towards this, the necessary conditions on the existence of delay-bounded connectivity are derived. To enhance network connectivity, the mobility-assisted data forwarding scheme is exploited, whose important design parameters, such as critical mobility radius, are derived. Moreover, the latency in wireless mobile networks is analyzed, which exhibits asymptotic linearity in the initial distance between mobile users.

In this thesis, we analyze the bandwidth requirements of MPEG-4 AVC video traffic and then propose and evaluate the accuracy of new MPEG-4 AVC video traffic models. First, we analyze the bandwidth requirements of the videos by comparing the statistical characteristics of the different frame types. We analyze their coefficient of variability, autocorrelation, and crosscorrelation in both short and long term. The Hurst parameter is also used to investigate the long range dependence of the video traces. We then provide an insight into B-frame dropping and its impact on the statistical characteristics of the video trace. This leads us to design two algorithms that predict the size of the B-frame and the size of the group of pictures (GOP) in the short-term. To evaluate the accuracy of the prediction, a model for the error is proposed. In a broadband cable network, B-frame size prediction can be employed by a cable headend to provision video bandwidth efficiently or more importantly, reduce bit rate variability and bandwidth requirements via selective B-frame dropping, thereby minimizing buffering requirements and packet losses at the set top box. It will be shown that the model provides highly accurate prediction, in particular for movies encoded in high quality resolution. The GOP size prediction can be used to provision bandwidth. We then enhance the B-frame and GOP size prediction models using a new scene change detector metric. Finally, we design an algorithm that predicts the size of different frame types in the long-term. Clearly, a long-term prediction algorithm may suffer degraded prediction accuracy and the higher complexity may result in higher latency. However, this is offset by the additional time available for long-term prediction and the need to forecast bandwidth usage well ahead of time in order to minimize packet losses during periods of peak bandwidth demands. We also analyze the impact of the video quality and the video standard on the accuracy of the model.

Thesis (MSc (Mathematical Sciences. Computer Science))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: Since 2002 data tra c has overtaken voice tra c in volume [1]. Telecom / Network operators still generate most of their income carrying voice tra c. There is however a huge revenue potential in delivering reliable guaranteed data services. Network survivability and recovery from network failures are integral to network reliability. Due to the nature of the Internet, recovery from link failures needs to be distributed and dynamic in order to be scalable. Link failure recovery schemes are evaluated in terms of the survivability of the network, the optimal use of network resources, scalability, and the recovery time of such schemes. The need for recovery time to be improved is highlighted by real-time data tra c such as VoIP and video services carried over the Internet. The goal of this thesis is to examine existing link failure recovery schemes and evaluate the need for their extension, and to evaluate the performance of the proposed link failure recovery schemes. i / AFRIKAANSE OPSOMMING: Sedert 2002 het data verkeer die stem verkeer in volume verbygesteek [1]. Telekommunikasie / netwerk operateurs genereer egter steeds die meeste van hul inkomste met stem verkeer. Netwerk oorlewing en die herstel van netwerk mislukkings is integraal tot netwerk stabiliteit. Die samestelling van die Internet noodsaak dat die herstel van skakel mislukkings verspreid en dinamies van natuur moet wees. Die herstel-skema van skakel mislukkings word evalueer in terme van die oorleefbaarheid van die netwerk, die mees e ektiewe benutting van network bronne, aanpasbaarheid, en die herstel tydperk van die skema. Die vinnig moontlikste herstel tydperk word genoodsaak deur oombliklike data verkeer soos VoIP en beeld dienste wat oor die Internet gedra word. The doel van hierdie tesis is om bestaande skakel mislukking herstel skemas te evalueer, en dan verder ondersoek in te stel na hul uitbreiding. Daarna word die voorgestelde skakel mislukking skema se e ektiwiteit gemeet.