Mobile Multimedia Streaming Research Articles

Soft Delivery: Survey on a New Paradigm for Wireless and Mobile Multimedia Streaming

The increasing demand for video streaming services is the key driver of modern wireless and mobile communications. Although many studies have designed digital-based delivery schemes to send video content over wireless and mobile networks, significant quality degradation, known as cliff and leveling effects, often occurs owing to fluctuating channel characteristics. In this article, we present a comprehensive summary of soft delivery, which is a new paradigm for wireless and mobile video streaming and discuss the future directions of soft delivery. Existing studies found that introducing multi-dimensional cosine transform, human vision system, and graph signal processing can make soft delivery schemes more effective in untethered immersive experiences, including virtual reality and volumetric media, than digital-based delivery schemes. In addition, this study finds that soft delivery has the potential to be a new standard to deliver deep neural network models and tactile information over wireless and mobile networks.

Design of a 5G Multimedia Broadcast Application Function Supporting Adaptive Error Recovery

The demand for mobile multimedia streaming services has been steadily growing in recent years. Mobile multimedia broadcasting addresses the shortage of radio resources but introduces a network error recovery problem. Retransmitting multimedia segments that are not correctly broadcast can cause service disruptions and increased service latency, affecting the quality of experience perceived by end users. With the advent of networking paradigms based on virtualization technologies, mobile networks have been enabled with more flexibility and agility to deploy innovative services that improve the utilization of available network resources. This paper discusses how mobile multimedia broadcast services can be designed to prevent service degradation by using the computing capabilities provided by multiaccess edge computing (MEC) platforms in the context of a 5G network architecture. An experimental platform has been developed to evaluate the feasibility of a MEC application to provide adaptive error recovery for multimedia broadcast services. The results of the experiments carried out show that the proposal provides a flexible mechanism that can be deployed at the network edge to lower the impact of transmission errors on latency and service disruptions.

Deep learning-based video quality enhancement for the new versatile video coding.

Multimedia IoT (M-IoT) is an emerging type of Internet of things (IoT) relaying multimedia data (images, videos, audio and speech, etc.). The rapid growth of M-IoT devices enables the creation of a massive volume of multimedia data with different characteristics and requirements. With the development of artificial intelligence (AI), AI-based multimedia IoT systems have been recently designed and deployed for various video-based services for contemporary daily life, like video surveillance with high definition (HD) and ultra-high definition (UHD) and mobile multimedia streaming. These new services need higher video quality in order to meet the quality of experience (QoE) required by the users. Versatile video coding (VVC) is the new video coding standard that achieves significant coding efficiency over its predecessor high-efficiency video coding (HEVC). Moreover, VVC can achieve up to 30% BD rate savings compared to HEVC. Inspired by the rapid advancements in deep learning, we propose in this paper a wide-activated squeeze-and-excitation deep convolutional neural network (WSE-DCNN) technique-based video quality enhancement for VVC. Therefore, we replace the conventional in-loop filtering in VVC by the proposed WSE-DCNN model that eliminates the compression artifacts in order to improve visual quality and hence increase the end user QoE. The obtained results prove that the proposed in-loop filtering technique achieves -2.85%, -8.89%, and -10.05% BD rate reduction for luma and both chroma components under random access configuration. Compared to the traditional CNN-based filtering approaches, the proposed WSE-DCNN-based in-loop filtering framework achieves efficient performance in terms of RD cost.

ICN based vehicle-to-cloud delivery for multimedia streaming in urban vehicular networks

Mobile multimedia streaming is an open topic in vehicular environment. Due to the high intermittent links, it has become a critical challenge to deliver high quality video streaming in vehicular networks. In this paper, we reform the Information Centric Networking (ICN) concept for multimedia delivery in urban vehicular networks. By leveraging the ICN perspective, we highlight that vehicular peers can obtain multimedia chunks via the vehicle-to-cloud (V2C) approach to improve the delivery quality. Based on this, we propose a lightweight multipath selection strategy to guide the network system to adaptively adjust the forwarding means. Extensive simulations show that the proposed solution can optimize the utilization of network paths, lighten network loads as well as avoid wasting resources.

Service-oriented mobile multimedia cooperative storing and delivery scheme based on opportunistic cloud coding and content-centric cloud compression

In order to improve the quality of multimedia communication and mobile users, the work efficiency of the cloud platform, the service-oriented mobile multimedia cooperative storing, and the delivery scheme were proposed based on opportunistic cloud coding and content-centric cloud compression. Firstly, according to the video frame and the multimedia content centric, the multimedia data compression algorithm was established based on time domain and frequency domain, which combined the image pixel scale and the component. Then, the opportunity cloud encoding program was proposed through the distortion scattering and the opportunity to cooperate with the cloud device control. Finally, the real-time transmission and cooperative feedback control of mobile multimedia streaming video content was proposed based on user requirements and service-driven demands. Experimental results show that the proposed scheme can provide high peak signal-to-noise ratio (PSNR) for large scale video frame transmission and keep high consistency and robustness from subjective experience to objective experience. In addition, the proposed scheme can significantly reduce the failure rate and improve the end-to-end communication performance.

Reliable Energy-Efficient Multilayer Mechanism with Realistic Battery Model and QoE Support in Wireless MANETs

Evolution in the telecommunications networks and the rapid advances made in wireless mobile communication networks, have taken computer networks to a new communication level. They now provide support for new mobile multimedia applications and are thus fostering the development of new network types and configurations. MANET is an important configuration of network for operations that employ mechanisms to enable dynamic self-configuration, self-optimization and self-healing, which is a challenging task for the routing protocols, new multimedia application and the battery energy consumption of wireless and mobile devices. These protocols are challenging because battery problems are more serious in this type of network and the existing protocols are not adapted to current problems, particularly mobile multimedia streaming, that can be found in most Internet flow. This paper proposes a reliable energy-efficient multilayer mechanism to address this to make improvements in the main current protocols. The proposal adds decision metrics to an energy-efficient computational intelligence technique based on Fuzzy-System with QoE, mobility and battery guarantees, choosing the best path in an efficient and accuracy way. The proposal has been evaluated in a network simulator.

A Novel Energy-Efficiency Social-Inspired Video Sharing Solution in Wireless Networks

Mobile multimedia streaming services provide rich-content visual resources for the mobile users via ubiquitous access to Internet. The video resource sharing focuses on the matching of appropriate resource supplier for the resource requesters and is a key issue for P2P-based video system scalability and user quality of experience. In this context, leveraging social-driven interaction between mobile users enables the discovery of common interests to improve video content sharing efficiency. In this paper, we propose a novel energy-efficiency social-inspired video sharing solution in wireless networks (ESVS). By the analysis of historical request behaviors of users, ESVS designs an estimation method of relationship between videos and groups the videos into a chain-based tree structure. Based on the constructed video tree, ESVS designs a hybrid resource lookup algorithm including push and pull and a communication quality-aware selection strategy of video suppliers, which improves the communication capacities between requesters and suppliers and reduces the network bandwidth consumption. Simulation results also show how ESVS achieves higher resource lookup success rate, lower startup delay, less packet loss rate, and lower maintenance cost than another state-of-the-art solution.

Socially aware mobile peer-to-peer communications for community multimedia streaming services

Mobile multimedia streaming services have become the main reason behind the latest increase in mobile data traffic worldwide. The enormous user base, frequency of data exchange, and demand for high-quality multimedia content open up new challenges to offer good QoS levels in mobile multimedia streaming systems. This article presents an innovative SMMC that integrates performance factors with aspects such as demand, socialization, mobility, and delivery. Simulation results demonstrate that SMMC achieves high content sharing efficiency and increased QoS levels.

An Integrated Predictive Mobile-Oriented Bandwidth-Reservation Framework to Support Mobile Multimedia Streaming

Bandwidth is an extremely valuable and scarce resource in wireless networks. Therefore, efficient bandwidth management is necessary to support service continuity, guarantee acceptable quality of service and ensure steady quality of experience for users of mobile multimedia streaming services. Indeed, the support of uniform streaming rate during the entire course of a streaming service, whereas the user is on the move is a challenging issue. In this paper, we propose a framework, together with schemes, which integrates user mobility prediction models with bandwidth availability prediction models to support the requirements of mobile multimedia services. More specifically, we propose schemes that predict paths to destinations, times when users will enter/exit cells along predicted paths, and available bandwidth in cells along predicted paths. With these predictions, a request for a mobile streaming service is accepted only when there is enough (predicted) available bandwidth, which is along the path to destination, to support the service. Simulation results show that the proposed approach outperforms existing bandwidth management schemes in better supporting mobile multimedia services.

3GPP Mobile Multimedia Streaming Standards [Standards in a Nutshell

Data rates offered by mobile networks are increasing, as are the capabilities of mobile devices. With this, mobile multimedia services are getting wider distribution. Traditional linear mobile TV services, where the viewer has to watch a scheduled TV program at the offered time, were initially dominating but other streaming services like Video on Demand, User-Generated Content (USG) services, or Internet streaming services are becoming more important. This article describes the 3rd Generation Partnership Project (3GPP) standards for mobile unicast multimedia streaming and how they are used in almost 200 mobile networks.

Improve QoS of Mobile Multimedia Streaming via Cross-Layer Predictive Packet Transmission over MIPv4

As the development of broadband technologies and diversified network applications, Internet apparently becomes a part of our daily life. People can enjoy various multimedia services such as VoD, VoIP, IPTV and online gaming through prevalent Internet access. Besides, as the technology advances of mobile devices and wireless networks, nomadic users can use portable devices such as PDAs and smartphones to connect Internet via wireless links. However, wireless Internet connections have deficiencies in performance and mobility to provide seamless services for QoS-restricted multimedia communications. In this paper, we propose an effective scheme called P3T (Pre-registration & Predictive Packet Transmission) to reduce quality degradation in mobile multimedia communications while handover to new networks. P3T couples an improved pre-registration scheme with cross-layer predictive packet transmission via same network interface. Both theoretic analysis and experimental results in real-time multimedia systems of VoIP and VoD services show that our proposed scheme can significantly reduce handoff latency in layer 3 and recover lost packets from handoff.

A robust method for soft IP handover

Multimedia streaming over wireless networks - often called mobile multimedia streaming lets users access music, movie, and news services at any time, regardless of location. Given that multimedia streaming is a key goal of third-generation and future wireless networks, vendors will soon deploy streaming clients in advanced mobile terminals. Current mobile terminals, however, fail to adequately support mobile multimedia communication because wireless networks have high packet-loss rates. To eliminate packet loss during handover, we use a packet path diversity scheme and an end-to-end bicasting mechanism that enables soft IP handover. To offset wireless errors, we use a forward error correction (FEC) scheme and embed it in the bicasting mechanism. Our bicasting method encodes the data stream and then splits it, providing more effective diversity than general bicasting, which sends the same data down both paths.' To support our method, we propose the mobile multimedia streaming protocol (MMSP), a new transport-layer protocol that supports multihoming and bicasting in combination with FEC.