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.

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 development of wireless networking technologies continues, it has been increasingly expected to support content-rich multimedia communications (e.g., video) in such networks. In this dissertation, we study the important problems of enhancing QoS support for video applications in wireless mesh networks and LTE networks. We begin our investigation with a video performance evaluation study in a wireless mesh test-bed. The goal is to clearly understand the nature of video streaming and its performance in wireless mesh networks. By extensive experiments in various scenarios we analyze the network parameters and settings which impact video performance. Compared with simulation or network-layer statistics based approaches, our investigation is directly focused on video quality in multi-hop scenarios. The experimental results better represent the characteristics of real networks and reveal the interesting aspects of video performance in mesh networks, which may benefit the design of efficient QoS solutions for multimedia services in wireless mesh networks. Next, we explore the interference issue in wireless mesh networks, and propose an interference-aware admission control and QoS routing scheme, towards enhancing video streaming experience in wireless mesh networks. Interference is characterized using a conflict graph based model. Nodes exchange their flow information periodically and compute their available residual bandwidth based on the local maximal clique constraints. Admission decision is made based on the residual bandwidth at each node. An on-demand routing scheme is implemented to explicitly incorporate the interference model in the route discovery process. By avoiding the "hot-spots" with severe interference, it discovers the routes with less interference and enhances video performance significantly. We also leverage MAC layer retransmission counts to design a combined queuing and routing scheme which achieves better video quality than the existing approaches. A case study is performed focusing on MAC layer retransmission, which helps us better understand the impacting factors on video quality in multi-hop mesh networks. Our scheme is proposed from a cross-layer perspective which leverages the information across network (routing) layer and link (MAC) layer. MAC layer retransmission count is exploited to guide the interface queue management for video packets as well as a metric to construct a retransmission-aware QoS routing scheme. In our approach, the upper layers are aware of the dynamic network status via retransmission count, so timely QoS decision can be made to enhance video quality effectively. For LTE networks, our focus is radio resource management. We first investigate the important problem of downlink resource allocation in recently enhanced LTE-Advanced systems where a newly added feature, carrier aggregation, provides more flexibility in resource allocation in addition to the existing resource block level packet scheduling. The resource allocation problem is formulated as a complex combinatorial problem with multiple constraints. We decompose this highly complex optimization problem and construct a two-tier resource allocation framework which incorporates dynamic component carrier assignment and novel backlog based scheduling schemes with intelligent link adaptation based on weighted CQI. The proposed schemes offer both better throughput and delay performance as well as user fairness. Finally, we address the downlink scheduling problem in LTE networks by directly optimizing video quality. Unlike the conventional scheduling rules which exploit network layer metrics, our scheme is directly targeted on optimizing application-layer video quality. Video quality optimized scheduling is formulated as a complex combinatorial optimization problem, and solved by exploiting a GA (genetic algorithm) based metaheuristic approach. The intrinsic strength of population based solution of GA offers a superior advantage for this type of scheduling problems. Simulation results demonstrate the effectiveness of GA based scheduling scheme compared with the well-known M-LWDF scheduling rule and the simulated annealing method. It can offer better video quality at the receiver within the required delay bound.

This volume constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019, held in Maribor, Slovenia, in July 2019. The 18 full papers presented in this volume were carefully reviewed and selected from a total of 31 submissions for inclusion in the proceedings. The papers cover a wide range of topics in swarm, evolutionary, memetic and other intelligent computing algorithms and their real world applications in problems selected from diverse domains of science and engineering.

Wireless video communications encompass a broad range of issues and opportunities that serve as the catalyst for technical innovations. To disseminate the most recent advances in this challenging yet exciting field, Advanced Video Communications over Wireless Networks provides an in-depth look at the fundamentals, recent technical achievements, challenges, and emerging trends in mobile and wireless video communications. The editors have carefully selected a panel of researchers with expertise in diverse aspects of wireless video communication to cover a wide spectrum of topics, including the underlying theoretical fundamentals associated with wireless video communications, the transmission schemes tailored to mobile and wireless networks, quality metrics, the architectures of practical systems, as well as some novel directions. They address future directions, including Quality-of-Experience in wireless video communications, video communications over future networks, and 3D video communications. The book presents a collection of tutorials, surveys, and original contributions, providing an up-to-date, accessible reference for further development of research and applications in mobile and wireless video communication systems. The range of coverage and depth of expertise make this book the go-to resource for facing current and future challenges in this field.

This insightful text presents a guide to video distribution networks (VDNs), providing illuminating perspectives on reducing power consumption in IP-based video networks from an authoritative selection of experts in the field. A particular focus is provided on aspects of architectures, models, Internet protocol television (IPTV), over-the-top (OTT) video content, video on demand (VoD) encoding and decoding, mobile terminals, wireless multimedia sensor networks (WMSNs), software defined networking (SDN), and techno-economic issues. Topics and features: reviews the fundamentals of video over IP distribution systems, and the trade-offs between network/service performance and energy efficiency in VDNs; describes the characterization of the main elements in a video distribution chain, and techniques to decrease energy consumption in software-based VoD encoding; introduces an approach to reduce power consumption in mobile terminals during video playback, and in data center networks using the SDN paradigm; discusses the strengths and limitations of different methods for measuring the energy consumption of mobile devices; proposes optimization methods to improve the energy efficiency of WMSNs, and a routing algorithm that reduces energy consumption while maintaining the bandwidth; presents an economic analysis of the savings yielded by approaches to minimize energy consumption of IPTV and OTT video content services. The broad coverage and practical insights offered in this timely volume will be of great value to all researchers, practitioners and students involved with computer and telecommunication systems.​

Energy efficiency is a key driver for the utilization of mobile-to-mobile cooperation in wireless networks. Delay-sensitive services such as layered video transmission require end-to-end delay bounds when mobile-to-mobile cooperation is employed. Due to the inherently stochastic nature of wireless fading channels, deterministic delay bounds are prohibitively difficult to guarantee. An alternative is to provide statistical guarantees using the concept of effective capacity/bandwidth by deriving quality of service (QoS) exponents for each video layer. Using this concept, we formulate and solve for the optimal resource allocation over general network flows involving sequential multicast and unicast to minimize the collective energy consumption in the network while guaranteeing a statistical end-to-end delay bound. Furthermore, we propose low complexity approximation algorithms for selecting the most energy-efficient distribution scheme from the entire set of directed acyclic graphs forming the candidate network flows based on the fading state on each link in the network. The candidate distribution schemes are encoded using Prufer sequences and resources are allocated on the selected network flow by solving the resource allocation optimization problem. The flow selection and resource allocation process is adapted in each time-frame by reconfiguring the service process on each network link according to the wireless channel variation. Considering realistic cooperation scenarios, results show that the proposed resource allocation and flow selection algorithms provide notable cooperation gains and small optimality gaps at low computational costs, thus, ensuring the feasibility of efficient allocation of wireless resources for real-time video services with QoS provisions.