Optimized scalable cache management for video streaming system

An important research issue in video streaming is how to efficiently utilize the network resources to provide clients instant access to multiple video objects. Caching strategy and transmission scheme are the two essential points inside the video streaming framework. Recent research efforts on them are not sufficient due to their inflexible support for scalable encoded video streams and heterogeneous requests from clients. In this paper, we propose an optimized caching strategy (OCS) and a scalable transmission scheme (STS) for scalable coded video streaming. By exploring the characteristics of video streaming workload and system design objectives, OCS and STS work efficiently to minimize both network bandwidth cost and user access latency. Firstly, we analyze the caching problem for the proxy-assisted video streaming system and derive a maneuverable caching scenario. Secondly, we develop an efficient transmission scheme for scalable coded videos. Thirdly, we formulate a multi-objective optimization model with closed-form expressions to obtain the optimized caching strategy. Finally, with designed algorithms, an excellent compromise between two competing objectives (minimizing the bandwidth cost and the access latency) is achieved. We start our evaluation by studying the optimized caching strategy for a single video object. Then we apply the strategy to multiple video objects and illustrate the tradeoff between the optimization objectives. Our evaluation results show that compared with other caching strategies, the proposed optimized scalable caching strategy can achieve a significant reduction in bandwidth cost with even a small proxy cache size. Meanwhile, the best performance (in terms of bandwidth cost) is obtained together with the proposed scalable batch-patching transmission scheme.

OCS: An effective caching scheme for video streaming on overlay networks

Video streaming is vital for many important applications such as distance learning, digital video libraries, and movie-on-demand. Since video streaming requires significant server and networking resources, caching has been used to reduce the demand on these resources. In this paper, we propose a novel collaboration scheme for video caching on overlay networks, called Overlay Caching Scheme (OCS), to further minimize service delays and loads placed on an overlay network for video streaming applications. OCS is not a centralized nor a hierarchical collaborative scheme. Despite its design simplicity, OCS effectively uses an aggregate storage space and capability of distributed overlay nodes to cache popular videos and serve nearby clients. Moreover, OCS is light-weight and adaptive to clients’ locations and request patterns. We also investigate other video caching techniques for overlay networks including both collaborative and non-collaborative ones. Compared with these techniques on topologies inspired from actual networks, OCS offers extremely low average service delays and approximately half the server load. OCS also offers smaller network load in most cases in our study.

Design and analysis of a variable bit rate caching algorithm for continuous media data

In this paper, the problem of caching continuous media data in a (main) memory and disk caching system is addressed. Caching schemes can significantly reduce the load on the network as well as on the servers, also the retrieval of documents from the cache requires short response time. In interval-level caching algorithms, an interval of data between two adjacent streams is the basic caching entity. In this paper, we design a novel algorithm, referred to as variable bit rate caching (VBRC) algorithm, which belongs to the interval-level caching algorithms. The proposed VBRC algorithm can be used in the system for memory caching or disk caching. VBRC can handle variable retrieval bandwidth as well as constant retrieval bandwidth . In designing the VBRC algorithm, we propose the strategies of reducing the number of switching operation, which will probably cause discontinuity of retrieving data. Also, we propose a just-in-time scheme for resource allocation in our VBRC algorithm and show that the caching performance in comparison with the reservation scheme adopted in the resource-based caching (RBC) algorithm is significantly improved. Our simulation study compares the recent and most popular generalized interval caching, RBC, and VBRC, on several influencing factors such as cache space size, cache I/O bandwidth, request arrival rate, and percentage of requests for large documents, with respect to the byte hit ratio and the number of switching operations. The simulation result confirms our analysis.

Streaming of scalable h.264 videos over the Internet

To investigate the benefits of scalable codecs in the case of rate adaptation problem, a streaming system for scalable H.264 videos has been implemented. The system considers congestion level in the network and buffer status at the client during adaptation process. The rate adaptation algorithm is content adaptive. It selects an appropriate substream from the video file by taking into account the motion dynamics of video. The performance of the system has been tested under congestion-free and congestion scenarios. The performance results indicate that the system reacts to congestion properly and can be used for Internet video streaming where losses occur unpredictably.

Exploiting client caches to build large Web caches

New demands brought by the continuing growth of the Internet will be met in part by more effective and comprehensive use of caching. This paper proposes to exploit client browser caches in the context of cooperative proxy caching by constructing the client caches within each organization (e.g., corporate networks) as a peer-to-peer (P2P) client cache. Via trace-driven simulations we evaluate the potential performance benefit of cooperative proxy caching with/without exploiting client caches. We show that exploiting client caches in cooperative proxy caching can significantly improve performance, particularly when the size of individual proxy caches is limited compared to the universe of Web objects. We further devise a cooperative hierarchical greedy-dual replacement algorithm (Hier-GD), which not only provides some cache coordination but also utilizes client caches. Through Hier-GD, we explore the design issues of how to exploit client caches in cooperative proxy caching to build large Web caches. We show that Hier-GD is technically practical and can potentially improve the performance of cooperative proxy caching by utilizing client caches.

A structured P2P network based on the small world phenomenon

In this paper, we propose a new structured P2P overlay network, named SW-Uinta(small-world). In order to reduce the routing latency, we firstly construct the Uinta network in which both physical characteristics of network and data semantic are considered. Furthermore, based on Uinta, a nondeterministic caching strategy is employed to allow for poly-logarithmic search time while having only a constant cache size. Compared with the deterministic caching strategy proposed by previous P2P systems, the nondeterministic caching strategy can reduce communication overhead for maintaining the routing cache table. Cache entries in the cache table of peer nodes can be updated by subsequent queries rather than only by running stabilization periodically. In the following, a novel cache replacement scheme, named the SW cache replacement scheme, is used to improve lookup performance, which has proved to satisfy the small-world principle. So we call this network SW-Uinta(small-world). After that, according to the theoretical analysis, it can be proved that SW-Uinta(small-world) can get O((log ² N)/k) search time with O(k) cache size. Lastly, the performance of SW-Uinta(small-world) is compared with those of other structured P2P networks such as Chord and Uinta. It shows that SW-Uinta(small-world) can achieve improved object lookup performance and reduce maintenance cost.

Building Scalable Wireless VoD Systems Through Efficient Management of Collocated Access Points

The growing need for ubiquitous access to video on demand (VoD) applications by large audiences has driven researches to build new scalable VoD systems that can guarantee Quality of Service (QoS) over wireless networks. In this paper, we propose and evaluate a novel system-level design that guarantees QoS by eliminating the service latency for short videos over IEEE 802.11 networks. Furthermore, our VoD system attains scalable performance by employing collocated access points (APs) coupled with an efficient association management of clients to the APs using a generic least-loaded-first heuristic on non-overlapping channels. Simulated results of our VoD system demonstrated that it achieved scalable performance due to its effective use of available bandwidth of the APs while supporting a low blockage rate for short videos up to 360 s. These results suggest that our VoD system can be an attractive solution for several classes of scalable VoD applications that require QoS guarantee such as movie trailers, news, video clips, and commercials.

PECOLE: P2P multimedia collaborative environment

PECOLE (Peer-to-pEer COLlaborative Environment) is a fully decentralized multimedia collaborative environment that supports a wide range of collaborative multimedia applications, including chat, shared browsing, shared telepointer, multipoint-to-multipoint audio/video conferencing and multilingual collaboration. PECOLE can intelligently run on very constrained resources, is highly resilient, scalable and does not rely on dedicated servers. Instead, PECOLE is built upon a Peer-to-Peer (P2P) overlay network, using SUN’s JXTA framework and SWT technology. In this paper, we present the architecture and implementation of PECOLE with the performance results of the tests we conducted.

P2Cast: peer-to-peer patching for video on demand service

Providing video on demand (VoD) service over the Internet in a scalable way is a challenging problem. In this paper, we propose P2Cast—an architecture that uses a peer-to-peer approach to cooperatively stream video using patching techniques, while only relying on unicast connections among peers. We address the following two key technical issues in P2Cast: (1) constructing an application overlay appropriate for streaming; and (2) providing continuous stream playback (without glitches) in the face of disruption from an early departing client. Our simulation experiments show that P2Cast can serve many more clients than traditional client-server unicast service, and that it generally out-performs multicast-based patching if clients can cache more than 10% of a stream’s initial portion. We handle disruptions by delaying the start of playback and applying the shifted forwarding technique. The threshold in P2Cast, i.e., the length of time during which arriving clients form a single session, can serve as a “knob” to adjust the balance between the scalability and the clients’ viewing quality.

Real time video frames allocation in mobile networks using cooperative pre-fetching

In this paper, we study the bandwidth allocation problem for serving video requests in a mobile real-time video player system. One of the main issues to maintain the quality of services (QoS) in mobile video playback is to ensure sufficient number of video frames available at the client side while a video is being played. However, due to the limited bandwidth of a mobile network and variable workload streaming video, this is not easy to achieve in practice. In addition, the communication link between mobile clients and a video server is subject to frequent errors and temporary disconnection. In this paper, we propose to use the notion of buffered bandwidth in addition to the network bandwidth to support real-time playback of videos at mobile clients. Based on this, we designed a bandwidth allocation scheme called Cooperative Pre-Fetching (CP) in which the amount of bandwidth to be allocated to serve a video request depends on the current buffer level of the video at the client relative to the target buffer level of the client. In determining the target buffer level, we consider the errors in communication to the client as well as the other clients who are concurrently served by the system. The buffered video frames at the clients are then used to minimize the impact of error in communications on the overall QoS of video playbacks in the whole system.

Video streaming over the internet with optimal bandwidth resource allocation

In this paper, an adaptive framework for video streaming over the Internet is presented. The framework is a joint design of packet scheduling and rate control with optimal bandwidth resource allocation. The transmission rate is dynamically adjusted to obtain maximal utilization of the client buffer and minimal allocation of the bandwidth. Under the constraint of the transmission rate, a prioritized packet scheduling is designed to provide a better visual quality of video frames. The packet scheduling is a refined bandwidth allocation which takes into account of varying importance of the different packets in a compressed video stream. Moreover, the proposed approach is scalable with increasing multimedia flows in the distributed Internet environment. Comparisons are made with the most current streaming approaches to evaluate the performance of the framework using the H.264 video codec. The extensive simulation results show that the average Peak Signal to Noise Ratio (PSNR) increases in our proposed approach. It provides a better quality of the decoded frames, and the quality of the decoded frames changes more smoothly. The achieved video quality among different users also has a lower fluctuation, which indicates a fair sharing of network resources.

A scalable signature scheme for video authentication

This paper addresses the problem of ensuring the integrity of a digital video and presents a scalable signature scheme for video authentication based on cryptographic secret sharing. The proposed method detects spatial cropping and temporal jittering in a video, yet is robust against frame dropping in the streaming video scenario. In our scheme, the authentication signature is compact and independent of the size of the video. Given a video, we identify the key frames based on differential energy between the frames. Considering video frames as shares, we compute the corresponding secret at three hierarchical levels. The master secret is used as digital signature to authenticate the video. The proposed signature scheme is scalable to three hierarchical levels of signature computation based on the needs of different scenarios. We provide extensive experimental results to show the utility of our technique in three different scenarios—streaming video, video identification and face tampering.

The “presence of others” in a virtual environment: different collaborative modalities with hybrid resources

The purpose of this study is to see in which forms and under which conditions social presence turns into collaboration. Eight couples were asked to find some objects in a virtual environment in which collaboration was allowed but not mandatory. The qualitative analysis of the video recordings shows that all participants resorted to collaboration in forms that were justified by the requirements of the task, the environmental affordances and the different expertise.

Multicast video-on-demand service in an enterprise network with client-assisted patching

Multicast Video-on-Demand (VoD) systems are scalable and  cheap-to-operate. In such systems, a single stream is shared by a batch of common user requests. In this research, we propose multicast communication technique in an Enterprise Network where multimedia data are stored in distributed servers. We consider a novel patching scheme called Client-Assisted Patching where clients’ buffer of a multicast group can be used to patch the missing portion of the clients who will request the same movie shortly. This scheme significantly reduces the server load without requiring larger client cache space than conventional patching schemes. Clients can join an existing multicast session without waiting for the next available server stream which reduces service latency. Moreover, the system is more scalable and cost effective than similar existing systems. Our simulation experiment confirms all these claims.

Proxy-assisted periodic broadcast for video streaming with multiple servers

Large scale video streaming over the Internet requires a large amount of resources such as server I/O bandwidth and network bandwidth. A number of video delivery techniques can be used to lower these requirements. Periodic broadcast by a central server combined with proxy caching offers a significant reduction of the aggregate network and server I/O bandwidth usage. However, the resources available to a single server are still limited. In this paper we propose a system with multiple geographically distributed servers. The problem of multiple servers for periodic broadcast is quite different from the problem of object location for multiple web servers. Multiple servers offer increased amount of resources and service availability and may potentially allow a further reduction of network bandwidth usage. On the other hand, the benefit of periodic broadcast mostly comes from high demand videos. With multiple servers holding a video, the demand of the video at each server is reduced. Therefore, it is a challenge to use multiple servers efficiently. We first analyze the dependence of the resource requirements on the number and locations of the servers. Based on the character of the function describing such a dependence, we formulate and solve the problem of video location and delivery, in a way that minimizes resource usage. We explore a trade-off between network and I/O bandwidth requirements. We evaluate our proposed solutions through a number of tests.

Extracting content from instructional videos by statistical modelling and classification

This paper presents a robust approach to extracting content from instructional videos for handwritten recognition, indexing and retrieval, and other e-learning applications. For the instructional videos of chalkboard presentations, retrieving the handwritten content (e.g., characters, drawings, figures) on boards is the first and prerequisite step towards further exploration of instructional video content. However, content extraction in instructional videos is still challenging due to video noise, non-uniformity of the color in board regions, light condition changes in a video session, camera movements, and unavoidable occlusions by instructors. To solve this problem, we first segment video frames into multiple regions and estimate the parameters of the board regions based on statistical analysis of the pixels in dominant regions. Then we accurately separate the board regions from irrelevant regions using a probabilistic classifier. Finally, we combine top-hat morphological processing with a gradient-based adaptive thresholding technique to retrieve content pixels from the board regions. Evaluation of the content extraction results on four full-length instructional videos shows the high performance of the proposed method. The extraction of content text facilitates the research on full exploitation of instructional videos, such as content enhancement, indexing, and retrieval.

Detecting repeats for video structuring

Television daily produces massive amounts of videos. Digital video is unfortunately an unstructured document in which it is very difficult to find any information. Television streams have however a strong and stable but hidden structure that we want to discover by detecting repeating objects in the video stream. This paper shows that television streams are actually highly redundant and that detecting repeats can be an effective way to detect the underlying structure of the video. A method for detecting these repetitions is presented here with an emphasis on the efficiency of the search in a large video corpus. Very good results are obtained both in terms of effectiveness (98% in recall and precision) as well as efficiency since one day of video is queried against a 3 weeks dataset in only 1 s.

Real-time stabilization of long range observation system turbulent video

The paper presents a real-time algorithm that compensates image distortions due to atmospheric turbulence in video sequences, while keeping the real moving objects in the video unharmed. The algorithm involves (1) generation of a “reference” frame, (2) estimation, for each incoming video frame, of a local image displacement map with respect to the reference frame, (3) segmentation of the displacement map into two classes: stationary and moving objects; (4) turbulence compensation of stationary objects. Experiments with both simulated and real-life sequences have shown that the restored videos, generated in real-time using standard computer hardware, exhibit excellent stability for stationary objects while retaining real motion.

Fast adaptive termination mode selection for H.264 scalable video coding

Although scalable video coding can achieve coding efficiencies comparable with single layer video coding, its computational complexity is higher due to its additional inter-layer prediction process. This paper presents a fast adaptive termination algorithm for mode selection to increase its computation speed while attempting to maintain its coding efficiency. The developed algorithm consists of the following three main steps which are applied not only to the enhancement layer but also to the base layer: a prediction step based on neighboring macroblocks, a first round check step, and a second round check step or refinement if failure occurs during the first round check. Comparison results with the existing algorithms are provided. The results obtained on various video sequences show that the introduced algorithm achieves about one-third reduction in the computation speed while generating more or less the same video quality.

Video scene segmentation and semantic representation using a novel scheme

Grouping video content into semantic segments and classifying semantic scenes into different types are the crucial processes to content-based video organization, management and retrieval. In this paper, a novel approach to automatically segment scenes and semantically represent scenes is proposed. Firstly, video shots are detected using a rough-to-fine algorithm. Secondly, key-frames within each shot are selected adaptively with hybrid features, and redundant key-frames are removed by template matching. Thirdly, spatio-temporal coherent shots are clustered into the same scene based on the temporal constraint of video content and visual similarity between shot activities. Finally, under the full analysis of typical characters on continuously recorded videos, scene content is semantically represented to satisfy human demand on video retrieval. The proposed algorithm has been performed on various genres of films and TV program. Promising experimental results show that the proposed method makes sense to efficient retrieval of interesting video content.