QoE-Oriented Cooperative Broadcast Optimization for Vehicular Video Streaming

The popularity of online vehicular video has caused enormous information requests in Internet of vehicles (IoV), which brings huge challenges to cellular networks. To alleviate the pressure of base station (BS), Roadside Units (RSUs) and vehicle peers are introduced to collaboratively provide broadcast services to vehicle requesters where vehicles act as both service providers and service requesters. In this paper, we propose an efficient framework leveraging scalable video coding (SVC) technique to improve quality of experience (QoE) from two perspectives: (1) maximizing the data volume received by all requesters and (2) determining buffer action based on playback fluency and average playback quality. For (1), potential providers cooperate to determine the precached video content and delivery policy with the consideration of vehicular mobility and wireless channel status. If one provider fails, other sources will complement to provide requested content delivery. Therefore, their cooperation can improve the QoE and enhance the service reliability. For (2), according to buffer occupancy status, vehicle requesters manage buffer action whether to buffer new segments or upgrade the enhancement level of unplayed segment. Furthermore, the optimization of the data volume is formulated as an integer nonlinear programming (INLP) problem, which can be converted into some linear integer programming subproblems through McCormick envelope method and Lagrange relaxation. Numerical simulation results show that our algorithm is effective in improving total data throughput and QoE.

An Adaptive Video Transmission Mechanism over MEC-Based Content-Centric Networks

The rapid growth of video traffic poses serious challenges to the current Internet. Content-Centric Networking (CCN) as a promising candidate has been proposed to reengineer the Internet architecture. The in-network caching and named content communication model of CCN can enhance the video streaming applications and reduce the network workload. Due to the bandwidth-consuming characteristic of video streaming, the aggressive transmission of video data will cause a reduction of overall network efficiency. In this paper, we present an adaptive video transmission mechanism over Mobile Edge Computing- (MEC-) based CCN. The computation and storage resources of the MEC server are utilized to facilitate the video delivery. Our mechanism adopts a scalable video coding scheme to adaptively control transmission rate to cope with the network condition variation. To analyse the equilibrium property of the proposed mechanism, an analytical model is deduced by using network utility function and convex programming. We also take into account the packet loss in wired and wireless links and present a MEC assistant loss recovery algorithm. The experiment results demonstrate the performance improvement of our proposed mechanism.

Streaming Coded Video in P2P Networks

This chapter discusses the state of the art in dealing with the resource optimization problem for smooth delivery of video across a peer to peer (P2P) network. It further discusses the properties of using different video coding techniques such as Scalable Video Coding (SVC) and Multiple Descriptive Coding (MDC) to overcome the playback latency in multimedia streaming and maintains an adequate quality of service (QoS) among the users. The problem can be summarized as follows; Given that a video is requested by a peer in the network, what properties of SVC and MDC can be exploited to deliver the video with the highest quality, least upload bandwidth and least delay from all participating peers. However, the solution to these problems is known to be NP hard. Hence, this chapter presents the state of the art in approximation algorithms or techniques that have been proposed to overcome these issues.

Hardware Efficient Hybrid Encoder for Video Surveillance Application

Extensive use of digital multimedia has led to the development of advance video processing techniques for development of multimedia applications. Application such as video surveillance requires 247 recording and streaming. So, the bandwidth and storage costs become significant. With introduction of video streaming over internet, where different kinds of end users request same content with different available bandwidth, it requires scalable video coding (SVC). These challenges can be overcome by developing new techniques to reduce redundancy in subsequent frames and to improve the coding efficiency. In this paper, overlapping weighted linear sum (OWLS) pre-processing method and its hardware architecture are proposed. It is implemented using field progrmmable gate array (FPGA) and the application specific integrated circuit (ASIC) is also developed using TSMC180nm technology standard cell library. Results show improvement in terms of power and area as compared to the existing work. In motion compensated temporal filtering (MCTF), wavelet transform is implemented by temporal filters. Architecture for 5/3 Lifting MCTF is also implemented and compared with baseline H.264 video codec. Simulation results show that the average peak signal to noise ratio (PSNR) improvement is 2.36[Formula: see text]dB. The MCTF design using 5/3 Lifting filter is synthesized for Virtex-5 FPGA and compared with the existing close-loop architecture with better performance.

Multipath Dynamic Adaptive Streaming over HTTP Using Scalable Video Coding in Software Defined Networking

Dynamic Adaptive Streaming over HTTP (DASH) offers adaptive and dynamic multimedia streaming solutions to heterogeneous end systems. However, it still faces many challenges in determining an appropriate rate adaptation technique to provide the best quality of experience (QoE) to the end systems. Most of the suggested approaches rely on servers or client-side heuristics to improve multimedia streaming QoE. Moreover, using evolving technologies such as Software Defined Networking (SDN) that provide a network overview, combined with Multipath Transmission Control Protocol (MPTCP), can enhance the QoE of streaming multimedia media based on scalable video coding (SVC). Therefore, we enhance our previous work and propose a Dynamic Multi Path Finder (DMPF) scheduler that determines optimal techniques to enhance QoE. DMPF scheduler is a part of the DMPF Scheduler Module (DSM) which runs as an application over the SDN controller. The DMPF scheduler accommodates maximum client requests while providing the basic representation of the media requested. We evaluate our implementation on real network topology and explore how SVC layers should be transferred over network topology. We also test the scheduler for network bandwidth usage. Through extensive simulations, we show clear trade-offs between the number of accommodated requests and the quality of the streaming. We conclude that it is better to schedule the layers of a request into the same path as much as possible than into multiple paths. Furthermore, these result would help service providers optimize their services.

XÂY DỰNG MÔ HÌNH QUAN HỆ GIỮA THỜI GIAN MÃ HÓA VÀ PHẠM VI TÌM KIẾM TẠO THÔNG TIN PHỤ CHO MÃ HÓA VIDEO PHÂN TÁN ỨNG DỤNG MẠNG CẢM BIẾN VIDEO

Trong những năm gần đây, mã hóa video phân tán liên lớp (Distributed Scalable Video Coding - DSVC) được nhiều nhà nghiên cứu quan tâm vì lợi ích của nó về độ phức tạp tính toán, khả năng phục hồi lỗi và khả năng mở rộng, vấn đề này rất quan trọng cho các ứng dụng video, như: Mạng cảm biến video không dây (Wireless Video Sensor Network - WVSN), Hệ thống video giám sát (Visual Surveillance System - VSS). Trong DSVC, việc tạo thông tin phụ (Side Information - SI) đóng một vai trò quan trọng vì nó ảnh hưởng trực tiếp đến hiệu năng nén DSVC và độ phức tạp tính toán của bộ mã hóa và bộ giải mã. Tuy nhiên, đối với nhiều ứng dụng WVSN và VSS, năng lượng của mỗi nút bị hạn chế, thường được cung cấp bằng Pin, khó thay thế và giảm dần theo thời gian, mặt khác cấu trúc phần cứng tại các nút cũng rất hạn chế cùng với giá thành thấp nên gây khó khăn trong việc truyền video trong thời gian thực. Để giải quyết vấn đề này, bài báo này đề xuất một giải pháp kiểm soát độ phức tạp tính toán tạo SI trong mã hóa DSVC. Để tạo SI, độ phức tạp tạo SI được mô hình hóa bằng cách sử dụng một mô hình tuyến tính, trong đó, các tham số mô hình được ước tính từ giá trị thử nghiệm và xây dựng bằng toán học. Để kiểm soát độ phức tạp tạo SI, tham số người dùng được xác định dựa trên nguồn năng lượng của WVSN, VSS. Các thử nghiệm được tiến hành cho các chuỗi video khác nhau đã cho thấy những lợi ích của giải pháp đề xuất, đặc biệt là trong kiểm soát độ phức tạp tính toán và hiệu suất nén.

A Novel Hybrid Optimization Algorithm for Scalable Video Coding in an SDN

Scalable Video Coding (SVC) is a powerful solution to video application over heterogeneous networks and diversified end users. In the recent years, works mostly concentrate on transported layers or path for a single layer in the Software-Defined Network (SDN). This paper proposes the Novel Hybrid Optimization Algorithm for Scalable Video Coding (NHO-SVC) based on Genetic Algorithm to select the layer and path simultaneously. The algorithm uses the 0/1 knapsack programming model to set up the model, predicts the network states by the Autoregressive Integrated Moving Average Model (ARIMA), and then, makes decision based on Genetic Algorithm.