Number Of Video Streams Research Articles

High performing multimedia transmission approach based on QoS support and admission control over IEEE 802.11e networks

SummaryHybrid coordination function controlled channel access (HCCA) is a medium to enhance quality of service (QoS) via the IEEE 802.11e standard. The main limitation of HCAA is that it is only efficient for constant bit rate (CBR) applications. This is due to the nature of its scheduler that allocates transmission opportunities (TXOPs) based on traffic stream (TS) specifications (TSPECs) that are determined during the traffic setup time. Variable bit rate (VBR) traffics used in HCCA have nondeterministic profile, making it not optimally and efficiently supported by HCCA. The result of this inefficiency is a deterioration of the transmission performance of multimedia data as well as a drop in the number of served QoS video traffics. We propose a novel approach to deal with this issue, which is the feedback‐based admission control unit (FACU). FACU works by optimizing the usage of extra bandwidth to ensure optimal transmission performance of multimedia data. FACU achieves this by exploiting piggybacked information concerning sequential video frames in order to accurately assign the TXOP. The proposed approach is evaluated by utilizing various video sequences. It is demonstrated that FACU maximizes the overall number of video streams and optimizes the overall usage of the network without having any adverse effects on the QoS constraints determined.

Video Stream Analysis in Clouds: An Object Detection and Classification Framework for High Performance Video Analytics

Object detection and classification are the basic tasks in video analytics and become the starting point for other complex applications. Traditional video analytics approaches are manual and time consuming. These are subjective due to the very involvement of human factor. We present a cloud based video analytics framework for scalable and robust analysis of video streams. The framework empowers an operator by automating the object detection and classification process from recorded video streams. An operator only specifies an analysis criteria and duration of video streams to analyse. The streams are then fetched from a cloud storage, decoded and analysed on the cloud. The framework executes compute intensive parts of the analysis to GPU powered servers in the cloud. Vehicle and face detection are presented as two case studies for evaluating the framework, with one month of data and a 15 node cloud. The framework reliably performed object detection and classification on the data, comprising of 21,600 video streams and 175 GB in size, in 6.52 hours. The GPU enabled deployment of the framework took 3 hours to perform analysis on the same number of video streams, thus making it at least twice as fast than the cloud deployment without GPUs.

Optimal media service selection scheme for mobile users in mobile cloud

Media cloud environments can provide a large number of multimedia services to mobile clients due to its flexibility and agility. However, a number of challenges need to be addressed so that these services are efficiently provided in terms of resources’ usage and energy consumption whilst improving the quality of service (QoS) and the user’s service satisfaction. This paper proposes a new media cloud distributed scheduling scheme that addresses these challenges, suitable for resource-intensive mobile application such as mobile video streaming. The proposed scheduling policy includes media service provisioning and cloud resource scheduling within the cloud datacenter, being able to jointly improve the mobile user’s satisfaction and the media cloud supplier’s revenue. Its aims are to minimize the service time, power consumption and costs for the service provider, through a convenient tradeoff of multiple QoS parameters and, consequently, increase the user’s satisfaction by reducing waiting times, service failure rate and power consumption of the mobile device. The validity of the proposed scheme is demonstrated by running experiments based on a practical use case of video streaming for mobile clients. The experiments were defined to allow to study the effects of request rate, video length, number of video streams and job size on the performance of the proposed media cloud distributed scheduling algorithm and compare it with related algorithms. The results show that proposed algorithm has better performance in terms of request failure rate, amount of energy consumed and response time.

Efficient Upstream Bandwidth Multiplexing for Cloud Video Recording Services

The upsurge of cloud video recording (CVR) has gained increasing attention from the general public and entrepreneurs. With live video records archived in the cloud, the CVR paradigm enables various smart services by keeping track of activities in the monitored region from anywhere at any time. However, the limited upstream bandwidth affects the quality of surveillance when multiple distributed cameras share the same upstream link. To solve the problem, this paper proposes an efficient upstream bandwidth multiplexing algorithm to intelligently allocate upstream bandwidth for each live video stream while maximizing the overall utility from the perspective of a CVR user. Specifically, we formulate the upstream bandwidth multiplexing problem as a constrained stochastic optimization problem, and apply the technique of hierarchical approximation to solve it efficiently. Our algorithm can be extended to take the priority of video streams into account and allocate more upstream bandwidth to video streams with higher priorities. We explicitly prove the approximation ratio of the proposed algorithm. In addition, we also conduct extensive trace-driven simulations to verify the effectiveness of our algorithm. The simulation results show that our algorithm improves the overall CVR user utility by over 20% compared with other alternatives, and the average utility per bandwidth unit is guaranteed to be stable even when the number of video streams increases.

Energy-Efficient Scalable Video Multicasting for Overlapping Groups in a Mobile WiMAX Network

Scalable video coding, together with adaptive modulation and coding, is a promising technique for providing real-time video multicast services on mobile stations (MSs) in heterogeneous channel conditions. On the other hand, since MSs are often powered by batteries, reducing the energy consumption of mobile devices is an important concern. In this paper, we study the problem of scalable video multicast scheduling in a mobile worldwide interoperability for microwave access (WiMAX) network with the objective of maximizing the multicast energy throughput. This problem has never been seriously studied when the assumption that different multicast groups may partially overlap is made. We prove that this problem is NP-complete. Our proposed solution, which is called energy-efficient multicast scheduling with adaptive modulation and coding (EEMS-AMC), consists of three modules, namely, online admission control, base-layer data scheduling, and enhancement-layer data scheduling. The admission control rules not only help the base station to admit the maximum number of video streams but ensure that the video data can be delivered to mobile users within the timeliness requirement as well. Moreover, EEMS-AMC adopts the greedy strategy to schedule base-layer data such that even in the worst-case scenario, the average duty cycle of admitted MSs can be within a bounded factor from the theoretical minimum. Finally, EEMS-AMC employs the metric “expected multicast throughput” to derive the proper modulation and coding scheme for each enhancement-layer data and employs the metric “marginal multicast energy throughput” to efficiently derive near-optimal enhancement-layer data scheduling. Simulation results exhibit that EEMS-AMC achieves relatively good performances in terms of multicast energy throughput and normalized total utility.

A Parallel Implementation of Singular Value Decomposition for Video-on-demand Services Design Using Principal Component Analysis

We have developed a mathematical model for video on demand server design based on principal component analysis. Singular value decomposition on the video correlation matrix is used to perform the PCA. The challenge is to counter the computational complexity, which grows proportionally to n3, where n is the number of video streams. We present a solution from high performance computing, which splits the problem up and computes it in parallel on a distributed memory system.

WEVCast: wireless eavesdropping video casting architecture to overcome standard multicast transmission in Wi-Fi networks

Service providers and popular applications are actively focused on delivering of video service to consumers over an all IP infrastructure but they rarely care about how contents are really delivered to end users. Services and applications are mostly designed to be enjoyed trough a generic broadband connection even if Wi-Fi is widely seen as the preferred access network to interconnect consumer devices. Wi-Fi has largely been optimized for unicast connections but has insufficient bandwidth to support a large number of video streams; on the other hand, multicast over Wi-Fi suffers from several well-known problems such as low data rate, high losses and unfairness respect to other contending unicast transmissions and the multimedia content delivery could be a stumbling block for providers and consumers alike. With the aim to develop a new solution that makes Wi-Fi video distribution more feasible and cost-effective, we propose a new mechanism, called WEVCast (Wireless Eavesdropping Video Casting), to improve multicast transmission of video contents over standard Wi-Fi networks. We implemented a quite realistic simulation framework and we evaluated the performance of our solution taking into account the perceived video quality experimented by end users. The obtained results confirm that the proposed strategy is very simple, robust, scalable and extremely compatible with all off-the-shelf wireless devices since our main goal was the Wi-Fi standard compliance.

Efficient delivery of on-demand video streams to heterogeneous receivers

The number of video streams that can be serviced concurrently is highly constrained by the required real-time and high-rate transfers of multimedia data. Resource sharing techniques, such as Batching, Patching, and Earliest Reachable Merge Target (ERMT), can be used to address this problem by utilizing the multicast facility, which allows multiple requests to share the same set of server and network resources. They assume, however, that all clients have the same available download bandwidth and buffer space. We study how to efficiently support clients with varying available download bandwidth and buffer space, while delivering data in a client-pull fashion using enhanced resource sharing. In particular, we propose three hybrid solutions to address the variability in the download bandwidth among clients: Simple Hybrid Solution (SHS), Adaptive Hybrid Solution (AHS), and Enhanced Hybrid Solution (EHS). SHS simply combines Batching with either Patching or ERMT, leading to two alternatives: SHS-P and SHS-E , respectively. Batching is used for clients with bandwidth lower than double the video playback rate, and Patching/ERMT is used for the rest. In contrast, AHS and EHS classify clients into multiple bandwidth classes and service them accordingly. AHS employs a new stream type, called adaptive stream , and EHS employs an enhanced adaptive stream type to serve clients with bandwidth capacities ranging between the video playback rate and double that rate. AHS and EHS employ adaptive streams or enhanced adaptive streams in conjunction with Batching and Patching or ERMT, leading to four possible schemes: AHS-P, AHS-E, EHS-P, and EHS-E. Moreover, we consider the variability of the available buffer space among clients. Furthermore, we study how the waiting playback requests for different videos can be scheduled for service in the heterogeneous environment, capturing the variations in both the client bandwidth and buffer space. We evaluate the effectiveness of the proposed solutions and analyze various scheduling policies through extensive simulation.

MeshVision: an adaptive wireless mesh network video surveillance system

The major surveillance camera manufacturers have begun incorporating wireless networking functionality into their products to enable wireless access. However, the video feeds from such cameras can only be accessed within the transmission range of the cameras. These cameras must be connected to backbone infrastructure in order to access them from more than one hop away. This network infrastructure is both time-consuming and expensive to install, making it impractical in many rapid deployment situations (e.g., to provide temporary surveillance at a crime scene). To overcome this problem, we propose the MeshVision system that incorporates wireless mesh network functionality directly into the cameras. Video streams can be pulled from any camera within a network of MeshVision cameras, irrespective of how many hops away that camera is. To manage the trade-off between video stream quality and the number of video streams that could be concurrently accessed over the network, MeshVision uses a bandwidth adaptation mechanism. This mechanism monitors the wireless network looking for drops in link quality or signs of congestion and adjusts the quality of existing video streams in order to reduce that congestion. A significant benefit of the approach is that it is of low cost, requiring only a software upgrade of the cameras.

Workload-Aware Resource Sharing and Cache Management for Scalable Video Streaming

The required real-time and high-rate transfers for multimedia data severely limit the number of video streams that can be delivered concurrently. Resource-sharing techniques address this problem and can be classified into two main classes: stream merging and periodic broadcasting. We evaluate through extensive simulation major resource-sharing techniques from the two classes, considering different service models and video workloads. We utilize this extensive analysis in developing a workload-aware hybrid solution (WAHS) that combines the advantages of the best performers among resource-sharing techniques. Moreover, we propose a statistical cache management (SCM) approach and derive analytical models for optimal cache allocation to reduce further the demands on the disk I/O when various resource sharing techniques are used.

A framework for calculating fundamental DVR performance limits

New systems have emerged that deliver hundreds of megabits per second of video to the home. This, coupled with deeper penetration of in-home video networking, will create demand for digital video recorder (DVR) performance to scale up dramatically as well. This paper outlines a simple analytic framework that can be used to estimate the performance of any DVR system, using either hard-disk drives or solid-state disk drives, in terms of both megabits per second and number of video streams. The framework also highlights the extent to which the maximum performance is constrained by the disk, by the host hardware, or by the host software.

The Rate Variability-Distortion (VD) Curve of Encoded Video and Its Impact on Statistical Multiplexing

Encoded video is expected to contribute a significant portion of the load on future communication systems and networks, which often employ statistical multiplexing. In such systems, the number of video streams that can be supported depends both on the mean bit rate as well as bit rate variability of the video streams. At the same time, the utility (revenue) earned from video streaming depends both on the number of supported video streams as well as their quality level. In this paper we examine the interplay between video quality, traffic variability, and utility for open-loop encoded video. We introduce the rate variability-distortion (VD) curve which relates the bit rate variability to the quality level of an encoded video. We find that the VD curve generally exhibits a characteristic hump behavior of first increasing, peaking, and subsequently decreasing variability for increasing quality. We examine the impact of video content characteristics, encoding parameters, and traffic smoothing on the VD behavior. We describe a methodology for assessing (i) the set of the video streams that can be supported with a statistical quality of service requirement, and (ii) the utility earned from video streaming over a link. This methodology is based on the rate-distortion and rate variability-distortion characteristics of the videos. We find that the statistical multiplexing gain and the utility as a function of the video quality level typically exhibit a hump similar to the VD curve.

Odyssey: a high‐performance clustered video server

AbstractVideo servers are essential in video‐on‐demand and other multimedia applications. In this paper, we present our high‐performance clustered CBR video server, Odyssey. Odyssey is a server connecting PCs with switched Ethernet. It provides efficient support for normal play and interactive browsing functions such as fast‐forward and fast‐backward. We designed a set of algorithms for scheduling, synchronization and admission control, which results in a high utilization of resources. Odyssey is able to deliver a large number of video streams. Copyright © 2003 John Wiley & Sons, Ltd.

Effective multi-program broadcasting of prerecorded video using VBR MPEG-2 coding

The tradeoff between picture quality and bandwidth usage is a prominent issue in the world of broadcasting. Since broadcasters are able to transmit multiple streams simultaneously in a channel, they face the challenge of guaranteeing the contracted picture quality required by each of the transmitted video streams while maximizing the number of video streams carried in each channel. We have developed an easy to implement MPEG-2 based multi-program video coding system suitable for digital TV broadcast, video on demand, and high definition TV over broadcast satellite networks with limited bandwidth. Compared to present broadcast systems and for the same level of contracted picture quality, our system greatly increases the number of video streams transmitted in each channel. As a result, either a large number of transponders can be freed to carry real-time broadcasting or the level of picture quality can be significantly increased. By switching from tape storage to video server technology, the need for numerous playback (VTR) systems at the headend is eliminated. In addition, the most of the complete MPEG-2 encoders are replaced by much less complex MPEG-2 transcoders. All this means a much more cost-effective solution for broadcast stations.

Delayed Frame Transmission Schemes for MPEG Videos in a Real-Time

In recent years, real-time systems are likely to be based on distributed architectures and utilize highly parallel algorithms. In such systems, cooperative tasks may be executed on different processors and communicate among each other via a high-speed network. With the growing demand on transmitting digital video in distributed multimedia applications, there is a need to study the on-time delivery of videos over a distributed system. Knowing the fact that unregulated transmission of MPEG video over a computer network may be hazardous to the network performance, in this paper, we exploit the characteristics of MPEG coded frame sequence and devise three transmission schemes for the MPEG video. The crux of the issue is to fully utilize the assigned bandwidth. In our schemes, the delayed frames mechanism can effectively utilize the assigned bandwidth and meet the objective of maximizing the number of video streams that can be supported in a timed token MAC network without sacrificing the video quality. Multiple classes of MPEG video are used in the study. These data are captured from real video programmes and we categorize these video clips according to their traffic burstiness and workload characteristics. The results reveal that by employing the Inter-stream Delayed Transmission Scheme, we could improve the performance by 66 to 166% depending on the availability of global information. When the technique is applied in an intra-stream level, we could improve the performance by 86%. When we combined these two schemes together, the performance improvement of the Total Delayed Transmission Scheme can be pushed to 178% which is a dramatic improvement over the original unregulated transmission scheme.

The effects of controlling capture on multimedia traffic for shared Ethernet systems

The IEEE 802.3 Ethernet standard is evolving to support much higher data rates and improved quality of service. Even low cost half?duplex CSMA/CD networks can be improved using an enhanced backwards?compatible collision arbitration algorithm known as the Binary Logarithmic Arbitration Method (BLAM) now being proposed as the IEEE 802.3w draft standard. BLAM is designed to co?exist fairly with the existing Binary Exponential Backoff (BEB) algorithm, while eliminating its short?term unfairness problems. In this paper, we focus on how BLAM improves Ethernet performance for multimedia data transport. Analytical, simulation, and prototype hardware experimental results using synthetic, trace, and actual measured traffic are presented. It is shown that BLAM Ethernets can support significantly greater numbers of video streams than existing BEB Ethernets and if the delivery requirements for the video traffic are not too strict, that BLAM Ethernets can even support video if the network is completely saturated with data traffic.

Spatio-temporal effects of multimedia objects storage and delivery for video-on-demand systems

As the number of video streams to be supported by a digital video delivery system (DVDS) increases, an improved understanding of the necessity for reliable and cost-efficient support for a considerable number of video streams (in the magnitude of tens of thousands), and the dependency largely on software capabilities emerges. Even in the presence of an optimal hardware configuration, or model, and associated costs, using software to exploit the underlying hardware capabilities is of paramount importance. Although a number of DVDSs have become operational, their ability to deliver the required services mainly depends on the small number of streams supported and the hardware trade-offs. It is imperative that current software developments account for the eventual scalability of the number of video streams without commensurate increase in hardware. In this paper, we present strategies for the management of video streams in order to maintain and satisfy their space and time requirements. We use a DVDS architectural model with functionally dichotomized nodes: a single-node partition is responsible for data retrieval, while the remaining partition of nodes accepts user requests, determines object locations, and routes requests through the network that connects both partitions. We present a detailed analysis of the issues related to queuing I/O requests and data buffering. The discussion includes the requirements for arranging and scheduling I/O requests and data buffers, with the objective of guaranteeing the required data availability rates for continuous media display.

Performance evaluation of ATM networks carrying constant and variable bit-rate video traffic

In this paper, we present the performance of asynchronous transfer mode (ATM) networks supporting audio/video traffic. The performance evaluation is done by means of a computer simulation model driven by real video traffic generated by encoding video sequences. We examine the glitching that occurs when the video information is not delivered on time at the receiver; we characterize various glitching quantities, such as the glitch duration, total number of macroblocks unavailable per glitch, and the maximum unavailable area per glitch. For various types of video contents, we compare the maximum number of constant bit-rate (CBR) and constant-quality variable bit-rate (CQ-VBR) video streams that can be supported by the network while meeting the same end-to-end delay constraint, the same level of encoded video quality, and the same glitch rate constraint. We show that when the video content is highly variable, many more CQ-VBR streams than CBR streams can be supported under given quality and delay constraints, while for relatively uniform video contents (as in a videoconferencing session), the number of CBR and CQ-VBR streams supportable is about the same. We also compare the results with those obtained for a 100Base-T Ethernet segment. We then consider heterogeneous traffic scenarios, and show that when video streams with different content, encoding scheme, and encoder control schemes are mixed, the results are at intermediate points compared to the homogeneous cases, and the maximum number of supportable streams of a given type can be determined in the presence of other types of video traffic by considering an effective bandwidth for each of the stream types. We consider multihop ATM network scenarios as well, and show that the number of video streams that can be supported on a given network node is very weakly dependent on the number of hops that the video streams traverse. Finally, we also consider scenarios with mixtures of video streams and bursty traffic, and determine the effect of bursty traffic load and burst size on the video performance.

Performance evaluation of 10Base-T and 100Base-T Ethernets carrying multimedia traffic

The performance of 10Base-T and 100Base-T Ethernet segments carrying audio/video traffic is presented. End-to-end delay requirements suitable for a wide range of multimedia applications are considered (ranging from 20-500 ms). Given the specific nature of the network considered and the maximum latency requirement, some data is lost. Data loss at the receiver causes quality degradations in the displayed video in the form of discontinuities, referred to as glitches. We define various quantities characterizing the glitches, namely, the total amount of information lost in glitches, their duration, and the rate at which glitches occur. We study these quantities for various network and traffic scenarios, using a computer simulation model driven by real video traffic generated by encoding video sequences. We also determine the maximum number of video streams that can be supported for given maximum delay requirement and glitch rate. We consider various types of video contents (video conferencing, motion pictures, commercials), two encoding schemes (H.261 and MPEG-1), and two encoder control schemes [constant bit rate (CBR) and constant-quality variable bit rate (CQ-VBR)] and compare their results. Furthermore, we consider scenarios with mixtures of video and data traffic (with various degrees of burstiness), and determine the effect of one traffic type over the other.

A scalable architecture for video-on-demand servers

One of the most important requirements to bring the interactive video-on-demand services to residential consumer use is the scalability of the video server. The design issues for a scalable video server is described and, according to these issues, the system architecture of the scalable video servers are proposed. The system uses ATM switching technology to scale up the dimension of the service. There are four major components within the proposed system, namely the server headend control (SHC) unit, the stream router, the video pumping unit (VPU) and distributed storage devices. The functions of each components is described and the key components in the system are the stream router and the VPU. Operations and performance limitations on the video pumping unit are given and the result shows that a single storage device can serve only a limited number of video streams. Finally the paper focuses on the stream router as it is used to connect multiple VPUs. Experimental results show that the proposed stream router can produce guaranteed throughput and bounded delay variance for video applications.