Optimal Resource Allocation For Distributed Video Communication

While most books on the subject focus on resource allocation in just one type of network, this book is the first to examine the common characteristics of multiple distributed video communication systems. Comprehensive and systematic, Optimal Resource Allocation for Distributed Video Communication presents a unified optimization framework for resour

As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins with a section on standards, fundamental methods, design issues, and typical architectures. It then focuses on the coding of video and multimedia content before covering multimedia search, retrieval, and management. After examining multimedia security, the book describes multimedia communications and networking and explains the architecture design and implementation for multimedia image and video processing. It concludes with a section on multimedia systems and applications. Written by some of the most prominent experts in the field, this updated edition provides readers with the latest research in multimedia processing and equips them with advanced techniques for the design of multimedia systems.

This exciting resource covers the fundamentals of wireless and PLC technologies. Different types of wireless and PLC technologies used for indoor IoT applications are described. The channel models for both wireless and power line communications are introduced, highlighting the main challenges for these types of communications inside the indoor environment. The book explores the hybrid technologies with television white space (TVWS), very high frequency (VHF) wireless technology, and broadband PLC (BPLC) for indoor high speed IoT networks. A TVWS standardized BPLC system is proposed, which integrates the requirement of primary user sensing and the permissible transmission power spectral density (PSD) for TVWS users into BPLC standard, regarding VHF band access. The hybrid ultra-high frequency (UHF) wireless-powerline sensor networks with a focus on enlarging the network lifetime via cross-layer optimization is presented. Hybrid video sensor networks (HVSNs) with high data rate requirement are explored. Through the joint design of video encoding rate, aggregate power consumption, channel access control, along with link rate allocation, a distributed algorithm is developed, which divides the computational burden among all nodes with much lower communication overhead. The effectiveness of the cross-layer designs are evaluated through extensive simulation results.

Mesh networking technologies allow a system of communication devices to communicate with each other over a dynamic and self-organizing wired or wireless network from everywhere at anytime. Large-scale mesh communication networks involve a large number of heterogeneous devices, each with different on-board computation speeds, energy supplies, and communication capabilities, communicating over the dynamic and unreliable networks. How to coordinate the resource utilization behaviors of these devices in a large-scale mesh network remains a challenging task. And an effective solution to this type of problems needs to meet the following three requirements: distributed, asynchronous, and non-convex. In this work, based on swarm intelligence principles, we develop a set of distributed and asynchronous schemes for resource allocation and performance optimization for a wide range of mesh networking-based applications, including particle swarm optimization (PSO) with convex mapping, decentralized PSO, distributed and asynchronous PSO, and energy efficient DAPSO. Our extensive experimental results in distributed resource allocation and performance optimization demonstrate that the proposed schemes work efficiently and robustly. Compared to existing algorithms, including gradient search and Lagrange optimization, the proposed approach had the advantage of faster convergence and the ability to handle generic network utility functions. Compared to centralized performance optimization schemes, the proposed approach significantly reduces communication overhead while achieving similar performance. The distributed algorithms for resource allocation and performance optimization provide analytical insights and important guidelines for practical design of large-scale video mesh networks.

This book presents a mathematical treatment of the radio resource allocation of modern cellular communications systems in contested environments. It focuses on fulfilling the quality of service requirements of the living applications on the user devices, which leverage the cellular system, and with attention to elevating the users’ quality of experience. The authors also address the congestion of the spectrum by allowing sharing with the band incumbents while providing with a quality-of-service-minded resource allocation in the network. The content is of particular interest to telecommunications scheduler experts in industry, communications applications academia, and graduate students whose paramount research deals with resource allocation and quality of service.

The prevalence of mobile devices has exponentially increased our ability to connect on an international level, swiftly accompanied by the popularity of communicating through the medium of multimedia. However, networking and processing requirements for exchanging images and videos are often orders of magnitude larger than those of text or even audio files. The research focuses on meeting and optimizing these pressing demands in the presence of competition for wireless network resources. Comprehensive solutions to energy-aware dual-path network utility maximization for crowdsourced image processing are derived and optimized. A delay resistant trace-based heuristic for distributed implementation that closely follows ideal algorithm behavior is developed. An iterative update solution to achieve maximum utility within a given time horizon using experimentally derived energy constraints is presented. Novel schemes for 5G network resource allocation and video streaming algorithms are provided. The research delivers a thorough analysis of all associated trade-offs in maximizing user Quality of Experience (QoE) while simultaneously minimizing associated energy consumption on mobile devices, as these goals are often in direct conflict with one another. Comparison of existing algorithms and proposed solutions are provided.

Advancements in broadband wireless networks and video compression tech- nologies have led to a tremendous increase in the demand for wireless multimedia services over recent years. Popular wireless transmission techniques enabling en- hanced throughput include orthogonal frequency division multiplexing (OFDM) while the recent video coding standard, namely the H.264/ AYC, enables up to twice the compression efficiency to be attained relative to previous video com- pression techniques. Regardless of these developments, the highly dynamic and unpredictable nature of wireless channels, along with the requirements for main- taining the quality of service (Q08) and seamless video playback for all users, impose severe constraints on the design of wireless multimedia systems. A video coding technique that has been developed for such environments is the scalable video coding (8YC), which allows parts of the encoded bitstream to be discarded in response to a drop in the channel quality. However, state-of-the-art resource allocation techniques for SYC transmission over the wireless medium suffer from high computational complexity. Low-complexity, sub-optimal alternatives, on the other hand, are not always adequate. Given the sparse nature of spectrum resources, and the paradigm shift in spectrum access with the advent of cognitive radio systems, it is evident that sub-optimal algorithms having large optimality gaps are not desired. In fact, such approaches would be in contradiction to the definition of spectrum efficient, cognitive radio systems. In this thesis, resource allocation schemes for the transmission of H.264 SYC over wireless networks are investigated. In particular, OFDM systems are consid- ered, including OFDM-based cognitive radio networks. Cross-layer optimisation techniques for fine grain scalable (FGS) video sequences are analysed. Although the problem is initially non-convex and has non-polynomial-time (NP) complex- ity, low complexity techniques are derived that lead to solutions very close to the optimal. Resource allocation schemes for coarse grain scalable (CGS) and medium grain scalable (MGS) sequences over OFDM-based cognitive systems are also investigated. As opposed to FGS, CGS/MGS do not allow an encoded bitstream to be truncated at random bit location. Consequently, new methods are derived that focus on this particular type of video coding. The presence of multiple antennas at the cognitive transmitter and their effect on the aggregate visual quality of all secondary users are also discussed. Furthermore, a joint call admission control (CAC) and resource allocation for the transmission of CGS and MGS video sequences over orthogonal frequency division multiple access (OFDMA) are analysed. This scheme considers the sce- narios where the available channel resources are not enough to support the video data of all users. Finally, rate-adaptation techniques for scalable video transmission over wire- less networks are presented. Rate-adaptation refers to the methods by which the encoding parameters of the video coding are adapted in response to the chan- nel conditions. Interestingly, it is shown that under a given channel condition, increasing the granularity of a scalable sequence lead to diminishing returns in terms of the rate achieved. Moreover, the transmission of scalable sequences over cognitive radio networks where perfect channel knowledge is not available is investigated. The effect of the granularity of the bitstream on the interference observed by incumbent users is also presented. It is shown that the probability of exceeding the interference threshold can be significantly reduced by proper specification of the video encoding parameters.