Performance Of Video Delivery Research Articles

A Multi-Channel Packet Scheduling Approach to Improving Video Delivery Performance in Vehicular Networks

When working with the Wireless Access in Vehicular Environment (WAVE) protocol stack, the multi-channel operation mechanism of the IEEE 1609.4 protocol may impact the overall network performance, especially when using video streaming applications. In general, packets delivered from the application layer during a Control Channel (CCH) time slot have to wait for transmission until the next Service Channel (SCH) time slot arrives. The accumulation of packets at the beginning of the latter time slot may introduce additional delays and higher contention when all the network nodes try, at the same time, to obtain access to the shared channel in order to send the delayed packets as soon as possible. In this work, we have analyzed these performance issues and proposed a new method, which we call SkipCCH, that helps the MAC layer to overcome the high contention produced by the packet transmission bursts at the beginning of every SCH slot. This high contention implies an increase in the number of packet losses, which directly impacts the overall network performance. With our proposal, streaming video in vehicular networks will provide a better quality of reconstructed video at the receiver side under the same network conditions. Furthermore, this method has particularly proven its benefits when working with Quality of Service (QoS) techniques, not only by increasing the received video quality but also because it avoids starvation of the lower-priority traffic.

Throughput-Based Mapping Algorithm for Video Streaming over IEEE 802.11e WLAN

IEEE 802.11e utilizes the Enhanced Distributed Channel Access (EDCA) protocol to provide quality of service (QoS) support over WLANs. However, under EDCA, all video data are allocated to the same access category (AC) queue, irrespective of their coding importance. Consequently, the quality of the transmitted video may be severely degraded under heavy traffic load conditions. The literature contains several queue mapping mechanisms based on the settings of the AC queues, such as contention window size, for improving the video transmission quality over IEEE 802.11e WLANs. However, these mechanisms fail to consider the effect of the dequeuing time on the video delivery performance. Accordingly, the present study proposes a new queue mapping algorithm, designated as the throughput-based mapping algorithm (TMA), for improving the video transmission quality and reducing the video delay by dynamically allocating the video data packets to different AC queues based on their length and throughput such that the probability of the dequeuing time being reduced is increased. In implementing the proposed approach, the throughputs of the AC queues are analyzed using two Markov chain models. The simulation results show that TMA outperforms previously proposed static and dynamic queue mapping schemes in terms of a reduced AC queue length, an improved PSNR (peak signal-to-noise ratio), and a shorter transmission delay.

Optimized video content delivery for mobile networks using the transformative computing model

It is a challenge for future mobile networks to cope with enormous video traffic due to bottlenecks of the backhaul capacity and spectrum shortages. To address this situation, we study a content delivery solution for video-on-demand (VoD) applications in orthogonal frequency division multiplexing (OFDM)-based mobile networks in this paper. As done in some transformative computing models, the proposed solution firstly collects the user and environment information, and then computes a global-optimized video delivery scheme based on the collected information. The video delivery scheme is orchestrated using a novel video delivery model that implements deep cooperation among video users and device-to-device (D2D) communications. Several orchestration algorithms are proposed to improve the performance of video delivery.

Social-Aware D2D Video Delivery Method Based on Mobility Similarity Measurement in 5G Ultra-Dense Network

The huge amounts of network traffic generated by the ultra-high-definition video playback of super-large-scale video users results in tremendous pressure for front-haul and back-haul in the 5G network, which brings severely negative influence for the large-scale deployment and scalability of video systems and video delivery performance (e.g. transmission delay and packet loss) related to user quality of experience. The direct D2D communications between mobile devices with adjacent position in geographical area can offloading huge video traffic into the underlying networks, which reduces load of cellular base station in the edge networks and relieves traffic pressure in the core networks. In this paper, we propose a novel Social-Aware D2D Video Delivery Method based on Rapid Sample-Efficient Measurement of Mobility Similarity in 5G Ultra-Dense Network (DMSEM). By investigation for one-hop D2D pair relationship, DMSEM builds a social state transition model of user movement, which makes use of encounter duration and shared video length between encountered users to define the state transition condition. A cluster algorithm of encounter events is proposed, which achieves initial clusters of encounter events by calculating similarity between encounter events from the two aspects of both variation rate of geographical distance between mobile users and encounter duration time. DMSEM makes use of the Fuzzy C-Means to refine the initial clusters and extracts encounter patterns of mobile users. DMSEM designs a sample-efficiency rapid recognition algorithm of encounter pattern, which can use small number of encounter distance samples to achieve fast heuristic recognition of encounter pattern. Extensive tests show how DMSEM achieves better results in comparison with other state-of-the-art solutions in terms of packet loss rate, average freeze time, cache utilization, average bitrate, buffer level and control overhead.

A Load Balancing Solution for Improving Video Quality in Loaded Wireless Network Conditions

There is an increasing user demand for high-quality content-rich multimedia services. Despite their advantages, current wireless networks in general and wireless mesh networks in particular have limitations in terms of quality of service (QoS) provisioning, especially when dealing with increased amounts of time sensitive traffic such as video. This paper presents video load balancing solution (ViLBaS), a load balancing-based mechanism which enhances delivery performance of video services over multi-hop wireless mesh networks and improves user quality of experience (QoE) levels. ViLBaS involves performance monitoring at the level of the nodes and load balancing by off-loading traffic from loaded nodes to less loaded neighboring nodes. Simulation-based results show how the proposed ViLBaS improves video delivery performance in terms of both QoS and QoE metrics [delay, throughput, packet loss, and peak signal-to-noise-ratio (PSNR)]. The comparison is performed against three other traditional approaches in different network topologies, for diverse video flow distributions, and different sizes for the video queue.

SVC Video Delivery in Cache-Enabled Wireless HetNet

In heterogeneous cellular network (HetNet), costly transmissions from the macro base stations can be reduced by caching popular videos at small base station and user equipment. In this paper, we consider the joint transmission scheduling and rate allocation problem of scalable video coding streaming over cache-enabled wireless HetNet. We formulate the joint optimization problem to maximum system capacity with an mixed-integer linear programming, and prove that finding the optimal solution is NP-hard. Heuristic solution was proposed based on an iterative algorithm focusing on transmission scheduling decision and rate allocation, where transmission capacity is allocated flexibly and the quality of service of users is satisfied. Simulation results have shown that the proposed scheme can significantly improve the video-delivery performance for all users, in comparison with existing schemes.

Video Streaming in Content-Centric Mobile Networks: Challenges and Solutions

The massive amounts of mobile traffic generated by the unprecedented demand for high-quality video content are fast approaching the communication capacity of current network infrastructures. Novel solutions are required, including using content- centric mobile networks (CCMNs), which make use of storage, computation, and bandwidth resources of the entire network to support traffic offloading and large-scale content sharing in wireless mobile networks. The unicast-based interest routing in CCMNs is known for fast content delivery with low resource consumption, but video information management and mobility of mobile nodes significantly influence the performance of video delivery. This article first reviews recent studies and discusses the research challenges for content distribution and delivery in CCMNs. The article then presents an innovative video streaming solution in CCMNs (VSCC), which proactively leverages a content-centric multi-region video content management method and a mobility-adaptive content-centric video delivery mechanism to improve the performance of video delivery. Simulation results demonstrate that VSCC achieves high video sharing efficiency and increased QoS levels in comparison with two state of the art approaches.

Superimposed Modulation for Soft Video Delivery With Hidden Resources

Analog-transmission-based soft video delivery suffers from the leveling-off effect when the allocated channel bandwidth is severely insufficient. Fortunately, with superimposed modulation, it is possible for analog traffic to share bandwidth with digital traffic. In this paper, we design and analyze such a hybrid digital-analog superimposed modulation (HDA-SIM) scheme for soft video delivery. Unlike previous work, we treat the bandwidth of competing digital traffic as hidden resources for the video delivery system. The key problem in this scheme is how to allocate the bandwidth and power resources among various modulation symbols so that we can improve the performance of video delivery without sacrificing the throughput of existing digital traffic. The resource allocation problem is formulated and the optimal solution under any given channel signal-to-noise ratio is derived. Based on the results, the sufficient and necessary condition for the video delivery system to achieve performance gain is given. In addition, we implement the proposed scheme for two state-of-the-art soft video delivery systems known as SoftCast and SharpCast. Both simulations and testbed evaluations show that the HDA-SIM version can achieve significant gains in the received video quality over their original designs.

Cross-Layer Fairness-Driven Concurrent Multipath Video Delivery Over Heterogeneous Wireless Networks

The growing availability of various wireless access technologies promotes increasing demand for mobile video applications. Stream control transmission protocol (SCTP)-based concurrent multipath transfer (CMT) improves the wireless video delivery performance with its parallel transmission and bandwidth (BW) aggregation features. However, the existing CMT solutions deployed at the transport layer only are not accurate enough due to lower layer uncertainties, such as variations of the wireless channel. In addition, CMT-based video transmission may use excessive BW in comparison with the popular Transmission Control Protocol (TCP)-based flows, which results in unfair sharing of network resources. This paper proposes a novel cross-layer fairness-driven (CL/FD) SCTP-based CMT solution (CMT-CL/FD) to improve video delivery performance, while remaining fair to the competing TCP flows. CMT-CL/FD utilizes a cross-layer approach to monitor and analyze path quality, which includes wireless channel measurements at the data-link layer and rate/BW estimations at the transport layer. Furthermore, an innovative window-based mechanism is applied for flow control to balance delivery fairness and efficiency. Finally, CMT-CL/FD intelligently distributes video data over different paths depending on their estimated quality to mitigate packet reordering and loss, under the constraint of TCP-friendly flow control. Simulation results show how CMT-CL/FD outperforms existing solutions in terms of both video delivery performance and TCP-friendliness.

Video Delivery Performance of a Large-Scale VoD System and the Implications on Content Delivery

Video delivery performance is the main factor that affects Internet video quality. Characterizing the video delivery performance, especially the delivery throughput, can help content providers as well as Internet service providers (ISPs) in system optimization and network planning. Based on a unique dataset consisting of 20 million video download speed measurements , this paper comprehensively studies the video delivery throughput of a large-scale commercial video-on- demand (VoD) system. We observe that user speed exhibits a large variation over time of day as well as across provincial locations. In particular, the worst performance of day is 30% lower than the peak performance . The analysis also reveals that video download speed has a notable impact on Internet video quality, which in turn influences user engagement . The impact, however, becomes limited when the speed increases beyond a certain threshold, which is mostly dependent on the video encoded bitrates. We further examine the interaction between Internet infrastructure and video delivery throughput using the linear regression model and find that crossing the ISP or regional network border yields 15–20% speed loss. Based on these observations , we finally evaluate the potential of edge caching and hybrid CDN-P2P in the improvement of video download performance and video quality.

Video delivery in heterogenous crans: architectures and strategies

Video traffic has become a major part of mobile data traffic, and will keep growing in the coming years. The performance of video delivery is fundamentally constrained by the structure of the underlying wireless networks. The recently proposed heterogeneous cloud access networks have been widely recognized as an inevitable evolution trend of the current cellular system toward the future 5G system, where multiple hybrid radio access technologies coexist to provide flexible access for mobile users. As a key enabling functional block for high-performance video delivery, a powerful centralized baseband processing unit pool is adopted to control all the radio access technologies, and possibly facilitate the video encoding and transmission, which opens up the potential to achieve higher throughput, lower traffic delay, and greater robustness compared to its basic baseband processing unit counterpart without central control functions. However, such a centralized control framework also raises many new research challenges to be addressed. In this article, we provide an overview of the state-of-the-art video delivery architectures and video packet transmission strategies in heterogeneous cloud radio access networks, with highlights on the networking architectures, transmission strategies, performance analysis, and design challenges. This article also sheds some light on the design principles for future big-dataoriented wireless networks.

Priority Scheduling for Multipath Video Transmission in WMSNS

In video data transmission over Wireless Multimedia Sensor Networks (WMSNs), in which network congestion and link failures are main characteristics, providing Quality-of-Service (QoS) is challenging. In such situation, using multipath routing protocols along with efficient packet scheduling can improve the performance of video delivery over sensor networks. In this paper we propose a new packet scheduling mechanism for multipath video transmission over WMSN. Since, different video frame types in a compressed video stream have different impact on the perceived video at the receiver; our proposed scheme for video packet scheduling is content aware that schedules transmission of different video packets over different paths. For this purpose, condition of each routing path is periodically evaluated and the high priority video packets are transmitted through high quality paths. Simulation results show that our proposed scheduling improves the quality of the perceived video at the receiver, considerably.