The integration of heterogeneous access networks is becoming a possible feature of 4G wireless networks. It is challenging to deliver the multimedia services over such integrated networks because of the discrepancy in the bandwidth of different networks. This thesis presents an adaptive approach that combines source rate adaptation and buffering to achieve high quality VBR video streaming with less quality variation over an integrated two-tier network. Statistical information of the residence time in each network or localization information are utilized to anticipate the handoff occurrence. The performance of this approach is analyzed under the CBR case using a Markov reward model. Simulation under the CBR and VBR cases is conducted for different types of network models. The results are compared with a dynamic programming algorithm as well as other naive or intuitive algorithms, and proved to be promising.

The integration of heterogeneous access networks is becoming a possible feature of 4G wireless networks. It is challenging to deliver the multimedia services over such integrated networks because of the discrepancy in the bandwidth of different networks. This thesis presents an adaptive approach that combines source rate adaptation and buffering to achieve high quality VBR video streaming with less quality variation over an integrated two-tier network. Statistical information of the residence time in each network or localization information are utilized to anticipate the handoff occurrence. The performance of this approach is analyzed under the CBR case using a Markov reward model. Simulation under the CBR and VBR cases is conducted for different types of network models. The results are compared with a dynamic programming algorithm as well as other naive or intuitive algorithms, and proved to be promising.

As the data rates supported by the physical layer increase, overheads increasingly dominate the throughput of wireless networks. A promising approach for reducing overheads is to group a number of frames together into one transmission. This can reduce the impact of overheads by sharing headers and the time spent waiting to gain access to the transmission floor. Traditional aggregation schemes require that frames that are aggregated all be destined to the same receiver. These approaches neglect the fact that transmissions are broadcast and a single transmission will potentially be received by many receivers. Thus, by taking advantage of the broadcast nature of wireless transmissions, overheads can be amortized over more data and achieve more performance gain. To show this, we design a series of MAC-based aggregation protocols that take advantage of rate adaptation and the broadcast nature of wireless transmissions. We first show the design of a system that can aggregate both unicast and broadcast frames. Further, the system can classify TCP ACK segments so that they can be aggregated with TCP data flowing in the opposite direction. Second, we develop a rate-adaptive frame aggregation scheme that allows us to find the best aggregation size by tracking the size based on received data frames and the data rate chosen by rate adaptation. Third, we develop a multi-destination frame aggregation scheme to aggregate broadcast frames and unicast frames that are destined for different receivers using delayed ACKs. Using a delayed ACK scheme allows multiple receivers to control transmission time of the ACKs. Finally, we extend multi-destination rate-adaptive frame aggregation to allow piggybacking of various types of metadata with user packets. This promises to lower the impact of metadata-based control protocols on data transport. A novel aspect of our work is that we implement and validate the designs not through simulation, but rather using our wireless node prototype, Hydra, which supports a high performance PHY based on 802.11n. To validate our designs, we conduct extensive experiments both on real and emulator-based channels and measure system performance. / text

Ad hoc networks have emerged recently as an important trend of future wireless systems. The evolving wireless networks are seriously challenging the traditional OSI layered design. In order to provide high capacity wireless access and support new multimedia network, the various OSI layers and network functions should be considered together while designing the network. In this thesis, we briefly discuss performance optimization challenges of ad hoc networks and cross-layer design. Ad hoc wireless networks were implemented by using Network Simulator NS-2 and the wireless physical, data link, dynamic source routing (DSR) routing protocol models have been included in the simulation. Simulations show that the performance begins to drop at the moderate offered load due to congestion. In addition, the mobility and fading cause the route failures and packet loss in wireless environment. To improve the performance for wireless networks, we implemented a congestion-aware cross-layer design in NS-2. The MAC layer adaptively selects a transmission data rate based on the channel signal strength information from physical layer and congestion information from network layer. The MAC layer utilization gathered at MAC layer is sent to DSR as a congestion aware routing metric for optimal route discovery. We modified the source codes of 802.11 MAC layer and DSR protocol. The simulations show that rate adaptation in MAC layer improves the network performance in terms of throughput, delivery ratio, and end-to-end delay; using congestion information from MAC layer in routing discovery improves the performance of the network benefited from overall network load balance.

This dissertation is composed of two independent studies: Cellular research and WBAN (Wireless Body Area Network) research. Both investigations are directed towards improving the system performance in wireless communication systems in terms of Quality of Service (QoS) and system capacity. For the Cellular research part, this dissertation will present novel user-specific QoS requirements as defined by their respective Mean Opinion Score (MOS) formulas, and associated schedulers for wireless applications and systems that optimize spectral allocation. User-specific QoS requirements are defined and several methods to make use of such requirements to maximum the spectral utilization are presented. Five User-Specific QoS Aware (USQA) schedulers are proposed that consider the user-specific QoS requirements in the allocation of spectral resources. Schedulers are introduced that dynamically adapt to the user-specific QoS requirements to improve quality as measured by the MOS, or the system capacity, or can improve both the quality and system capacity. Due to the different cell deployment arrangements and inter-cell interference in heterogeneous networks in comparison to homogeneous networks, the USQA scheduling is also analyzed and the system performance is evaluated in such networks. Throughput improvements of File Transfer Protocol (FTP) applications benefiting from the rate adaptation and MAC (Media Access Control) scheduling algorithms for video applications that incorporate user-specific QoS requirements to improve system capacity are demonstrated. Another novel approach recognizes that the user-specific frequency sensitivity can be used to improve capacity. There is considerable variation in the audible range of frequencies that can be perceived by individuals, especially at the high frequency end, which is primarily affected by a gradual decline with age. This can be utilized to improve the system performance by personalizing the VoIP codecs and decreasing the user's source data rate for people from an older age group and thus increase the system capacity. Given the potentially substantial system performance gain resulting from the USQA schedulers, it is critical to analyze their feasibility and complexity in practical LTE (4G cellular) and future wireless systems. From the LTE system perspective, LTE QoS end-to-end signaling procedures are addressed, and corresponding protocol adaptations are analyzed in order to support the USQA schedulers. In addition, the optimal scheduling period is analyzed that trades off between performance gain and implementation complexity. In the WBAN research, MIMO (Multiple Input Multiple Output) in vivo antenna technologies are introduced and are motivated by the high data rate requirements of wirelessly transmitted low-delay High Definition (HD) video during Minimally Invasive Surgery (MIS). MIMO in vivo technologies are proposed to be used in the in vivo environments to enhance and determine the maximum data transmission rate while satisfying the Specific Absorption Rate (SAR) power limitations. Various factors are considered in the MIMO in vivo study including antenna separation, antenna angular positions, human body size, and system bandwidth to determinate the maximum data rate that can be supported.

Ad hoc networks are becoming an interesting research area, as they inher-ently support unique network applications for the wireless communications in a rug-ged environment, which requires rapid deployment and is difficult to be provided by an infrastructure network. Many issues need to be addressed for the ad hoc networks. In this dissertation, we propose an efficient distributed coordination function, a dynamic rate adaptation and fragmentation scheme, and a simultaneous frame transmission scheme on the media access control protocol to enhance the power conservation of mobile hosts and to im-prove the network throughput of an ad hoc network. Extensive simulations are studied to evaluate the improvement of the proposed schemes. The results of the simulations exhibit significant improvement to the stan-dard access control protocol. Not only the improvement of the throughput of the ad hoc networks, but also the conservation of the battery power of the mobile hosts were achieved with our schemes.

With the advent of mobile Internet the amount of time people spend with multimedia applications in the mobile environment is surging and demand for high quality multimedia data over the Internet in the mobile environment is growing rapidly. However the mobile environment is significantly more unfriendly than the wired environment for multimedia applications in many ways. Network resources are limited and the condition is harder to predict. Also multimedia applications are generally delay intolerant and bandwidth demanding, and with users moving, their demand could be much more dynamic and harder to anticipate. Due to such reasons many existing mobile multimedia applications show unsatisfactory performance in the mobile environment. We target three multimedia content delivery applications and optimize with limited and unpredictable network conditions typical in the mobile Internet environment. Vehicular networks have emerged from the strong desire to communicate on the move. We explore the potential of supporting high-bandwidth applications such as video streaming in vehicular networks. Challenges include limited and expensive cellular network, etc. Internet video conferencing has become popular over the past few years, but supporting high-quality large video conferences at a low cost remains a significant challenge due to stringent performance requirements, limited and heterogeneous client. We develop a simple yet effective Valiant multicast routing to select application-layer routes and adapt streaming rates according to dynamically changing network condition in a swift and lightweight way enough to be implemented on mobile devices. Bitrate adaptive video streaming is rapidly gaining popularity. However recent measurements show weaknesses in bitrate selection strategies implemented in today's streaming players especially in the mobile environment. We propose a novel rate adaptation scheme that classifies the network condition into stable and unstable periods and optimizes video quality with different strategies based on the classification. / text

Video streaming applications over best-effort networks, such as the Internet, have become very popular among Internet users. Watching live sports and news, renting movies, watching clips online, making video calls, and participating in videoconferences are typical video applications that millions of people use daily. One of the most challenging aspects of video communication is the proper transmission of video in various network bandwidth conditions. Currently, various devices with different processing powers and various connection speeds (2G, 3G, Wi-Fi, and LTE) are used to access video over the Internet, which offers best-effort services only. Skype, ooVoo, Yahoo Messenger, and Zoom are some well-known applications employed on a daily basis by people throughout the world; however, best-effort networks are characterized by dynamic and unpredictable changes in the available bandwidth, which adversely affect the quality of the video. For the average consumer, there is no guarantee of receiving an exact amount of bandwidth for sending or receiving video data. Therefore, the video delivery system must use a bandwidth adaptation mechanism to deliver video content properly. Otherwise, bandwidth variations will lead to degradation in video quality or, in the worst case, disrupt the entire service. This is especially problematic for videoconferencing (VC) because of the bulkiness of the video, the stringent bandwidth demands, and the delay constraints. Furthermore, for business grade VC, which uses high definition videoconferencing (HDVC), user expectations regarding video quality are much higher than they are for ordinary VC. To manage network fluctuations and handle the video traffic, two major components in the system should be improved: the video encoder and the congestion control. The video encoder is responsible for compressing raw video captured by a camera and generating a bitstream. In addition to the efficiency of the encoder and compression speed, its output flow is also important. Though the nature of video content may make it impossible to generate a constant bitstream for a long period of time, the encoder must generate a flow around the given bitrate. While the encoder generates the video traffic around the given bitrate, congestion management plays a key role in determining the current available bandwidth. This can be done by analyzing the statistics of the sent/received packets, applying mathematical models, updating parameters, and informing the encoder. The performance of the whole system is related to the in-line collaboration of the encoder and the congestion management, in which the congestion control system detects and calculates the available bandwidth for a specific period of time, preferably per incoming packet, and informs rate control (RC) to adapt its bitrate in a reasonable time frame, so that the network oscillations do not affect the perceived quality on the decoder side and do not impose adverse effects on the video session. To address these problems, this thesis proposes a collaborative management architecture that monitors the network situation and manages the encoded video rate. The goal of this architecture is twofold: First, it aims to monitor the available network bandwidth, to predict network behavior and to pass that information to the encoder. So encoder can encode a suitable video bitrate. Second, by using a smart rate controller, it aims for an optimal adaptation of the encoder output bitrate to the bitrate determined by congestion control. Merging RC operations and network congestion management, to provide a reliable infrastructure for HDVC over the Internet, represents a unique approach. The primary motivation behind this project is that by applying videoconference features, which are explained in the rate controller and congestion management chapter, the HDVC application becomes feasible and reliable for the business grade application even in the best-effort networks such as the Internet.

Current wireless networks still employ techniques originally designed for their xed wired counterparts. These techniques make assumptions (such as a xed topology, a static enviroment and non-mobile nodes) that are no longer valid in the wireless communication environment. Furthermore, the techniques and protocols used in wireless networks should take the number of users of a network into consideration, since the channel is a shared and limited resource. This study deals with nding an optimal solution to resource allocation in wireless mesh networks. These networks require a solution to fair and optimal resource allocation that is decentralised and self-con guring, as users in such networks do not submit to a central authority. The solution presented is comprised of two sections. The rst section nds the optimal rate allocation, by making use of a heuristic. The heuristic was developed by means of a non-linear mixed integer mathematical formulation. This heuristic nds a feasible rate region that conforms to the set of constraints set forth by the wireless communication channel. The second section nds a fair allocation of rates among all the users in the network. This section is based on a game theory framework, used for modelling the interaction observed between the users. The fairness model is de ned in strategic form as a repeated game with an in nite horizon. The rate adaptation heuristic and fairness model employs a novel and e ective information distribution technique. The technique makes use of the optimized link state routing protocol for information distribution, which reduces the overhead induced by utilising multi-point relays. In addition, a novel technique for enforcing cooperation between users in a network is presented. This technique is based on the Folk theorem and ensures cooperation by threat of punishment. The punishment, in turn, is executed in the form of banishment from the network. The study describes the performance of the rate adaptation heuristic and fairness model when subject to xed and randomised topologies. The xed topologies were designed to control the amount of interference that a user would experience. Although these xed topologies might not seem to re ect a real-world scenario, they provide a reasonable framework for comparison. The randomised network topology is introduced to more accurately represent a real-world scenario. Furthermore, the randomised network topologies consist of a signi cant number of users, illustrating the scalability of the solution. Both data and voice tra c have been applied to the rate adaptation heuristic and fairness model. It is shown that the heuristic e ectively reduces the packet loss ratio which drops below 5% after about 15 seconds for all xed topologies. Furthermore, it is shown that the solution is near-optimal in terms of data rate and that a fair allocation of data rates among all nodes is achieved. When considering voice tra c, an increase of 10% in terms of data rate is observed compared to data tra c. The heuristic is successfully applied to large networks, demonstrating the scalability of the implementation. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / unrestricted

Over the past few years, the surge in VR (Virtual Reality) video traffic on networks has been remarkable. Nonetheless, a key challenge remains: ensuring a top-notch quality of experience (QoE) for VR video playback, especially when network bandwidth is limited. Prior studies have mainly focused on tile-based adaptive bitrate (ABR) streaming operating at the application layer on the server/client side to improve QoE, using single viewport prediction to conserve bandwidth. However, single-viewpoint prediction models face limitations due to uncertainties linked with head movement, making it difficult to handle sudden user motions effectively. To overcome these constraints, we propose a lightweight multimodal spatial-temporal transformer architecture, which generates multiple viewpoint trajectories and their corresponding probabilities while leveraging historical trajectory information. Consequently, we introduce a multi-agent reinforcement learning (MARL)-based ABR algorithm that capitalizes on multiple viewport prediction for VR video streaming at the application layer. Our algorithm strives to optimize various QoE objectives under diverse network conditions. To address the ABR problem, we formulate it as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) problem. To tackle this effectively, we develop a MAPPO (Multi-Agent Proximal Policy Optimization) algorithm within a centralized training and decentralized execution (CTDE) framework. Meanwhile, we also improve QoE at the network layer by utilizing network resources in different network nodes during VR video streaming. We present an innovative system called tile-weighted rate-distortion (TWRD) packet scheduling optimization, which takes advantage of viewpoint prediction. The system dynamically assigns weights to tiles and their corresponding packets using the probability of viewpoint prediction. Due to limited bandwidth, the problem of packet scheduling arises, requiring the determination of which packets should be dropped. To address this challenge, we formulate the problem as an optimization task, taking into account error propagation in the video. Our system leverages the weighted rate-distortion information of packets and applies dynamic programming techniques to design an optimal packet scheduling scheme. By selectively dropping packets at network nodes, our proposed system effectively reduces network congestion and enhances the overall performance of VR video streaming systems operating within bandwidth limitations.