Broadcasting scheme with low client buffers and bandwidths for video-on-demand applications

Efficient data broadcasting is independent of request arrivals, and is thus highly promising when transmitting popular videos. A conventionally adopted broadcasting method is periodic broadcasting, which divides a popular video into segments, which are then simultaneously broadcast on different data channels. Once clients want to watch the video, they download the segments from these channels. The skyscraper broadcasting (SkB) scheme supports clients with small bandwidths. An SkB client requires only two-channel bandwidths to receive video segments. This work proposes a reverse SkB (RSkB) scheme, which extends SkB by reducing buffering spaces. The RSkB is mathematically shown to achieve on-time video delivery and two-channel client bandwidths. A formula for determining the maximum number of segments buffered by an RSkB client is presented. Finally, an analysis of RSkB reveals that its client buffer requirements are usually 25–37% lower than SkB. Extensive simulations of RSkB further demonstrate that RSkB yields lower client buffer demand than other proposed systems.

An enhanced client-centric approach for efficient video broadcast

Periodic broadcast is a cost-effective solution for large-scale distribution of popular videos. Regardless of the number of video requests, this strategy guarantees a constant worst service latency to all clients, making it possible to serve a large community with a minimal amount of broadcast bandwidth. Although many efficient periodic broadcast techniques have been proposed, most of them impose rigid requirements on client receiving bandwidth. They either demand clients to have the same bandwidth as the video server, or limit them to receive no more than two video streams at any one time. In our previous work, we addressed this problem with a Client-Centric Approach (CCA). This scheme takes into consideration both server broadcast bandwidth and client receiving bandwidth and allows clients to use all their receiving capability for prefetching broadcast data. As a result, given a fixed broadcast bandwidth, a shorter broadcast period can be achieved with an improved client communication capability. In this paper, we present an enhanced version of CCA to further leverage client bandwidth for more efficient video broadcast. The new scheme reduces the broadcast latency up to 50% as compared to CCA. We prove the correctness of this new technique and provide an analytical evaluation to show its performance advantage as compared with some existing techniques.

Periodic broadcast with dynamic server selection

Service replication is an effective way to address resource requirements and resource availability problem. Dynamic service selection enables clients to choose a server offering the best performance. Proper server selection is especially important for video streaming over the Internet due to its high bandwidth requirements. However, given the length of a typical video transmission, the server priorly selected may no longer be an optimal one for the duration of the entire transmission. More importantly, a server may fail during the transmission of a video. In this paper we examine the possibility of switching to another server during an on-going transmission for Periodic Broadcast schemes. Due to the timing requirements typical for Periodic Broadcast the server switch may cause playback disruptions. We analyze the magnitude of the problem and propose an easy to implement solution. We define the criteria, additional to the bandwidth availability for example, according to which a new server should be selected. The client is also required to delay its playback by the amount of time bounded by the server transmission offset. In addition, we propose an alternative method to ensure uninterrupted playback that relies on proxy caching. Simulation results show that our approach can significantly reduce the likelihood of playback disruptions.

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.

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.

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.

Throughput optimization for video streaming proxy servers based on video staging

A video streaming proxy server needs to handle hundreds of simultaneous connections between media servers and clients. Inside, every video arrived at the server and delivered from it follows a specific arrival and delivery schedule. While arrival schedules compete for incoming network bandwidth, delivery schedules compete for outgoing network bandwidth. As a result, a proxy server has to provide sufficient buffer and disk cache for storage, together with memory space, disk space and disk bandwidth. In order to optimize the throughput, a proxy server has to govern the usage of these resources. In this paper, we first analyze the property of a traditional smoothing algorithm and a video staging algorithm. Then we develop, based on the smoothing algorithm, a video staging algorithm for video streaming proxy servers. This algorithm allows us to devise an arrival schedule based on the delivery schedule. Under this arrival and delivery schedule pair, we can achieve a better resource utilization rate gracefully between different parameter sets. It is also interesting to note that the usage of the resources such as network bandwidth, disk bandwidth and memory space becomes interchangeable. It provides the basis for inter-resource scheduling to further improve the throughput of a video streaming proxy server system.

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.

Dynamically adjusting MPEG4 video streams based on network bandwidth

In the paper, we try to find a method that can service more users in a video-on-demand (VoD) system, based on MPEG-4 object streams. The characteristics of object segmentation made on MPEG-4 videos can be utilized to reduce re-transmission of the same objects, and then the saved bandwidth can be used to service more users. However, some thresholds must be analyzed first to maintain the acceptable quality of services (QoS) requested by users, when reducing unnecessary object transmission on one side. Thus, according to the defined thresholds, we propose a dynamically adjusting algorithm to coordinate the object streams between the server and clients. The server not only allocates network bandwidth, but also adjusts ever-allocated QoS appropriately using a degrading and upgrading strategy, based on the current network status. Lastly, through the simulation, we found that our method has better performance than the other three methods owing to its flexibility to the network status.

EXEM: Efficient XML data exchange management for mobile applications

In the past decade, the number of mobile devices has increased significantly. These devices are in turn showing more computational capabilities. It is therefore possible to envision a near future where client applications may be deployed on these devices. There are, however, constraints that hinder this deployment, especially the limited communication bandwidth and storage space available. This paper describes the Efficient XML Data Exchange Manager (EXEM) that combines context-dependent lossy and lossless compression mechanisms used to support lightweight exchange of objects in XML format between server and client applications. The lossy compression mechanism reduces the size of XML messages by using known information about the application. The lossless compression mechanism decouples data and metadata (compression dictionary) content. We illustrate the use of EXEM with a prototype implementation of the lossless compression mechanism that shows the optimization of the available resources on the server and the mobile client. These experimental results demonstrate the efficiency of the EXEM approach for XML data exchange in the context of mobile application development.

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.

Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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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.

Adaptation of proxy certificates to non-repudiation protocol of agent-based mobile payment systems

Non-repudiation of a mobile payment transaction ensures that when a buyer (B) sends some messages to a seller (S), neither B nor S can deny having participated in this transaction. An evidence of a transaction is generated by wireless PKI mechanism such that B and S cannot repudiate sending and receiving the purchase order respectively. The buyer generates a mobile agent which carries encrypted purchase order to the seller. This mobile agent is also issued a proxy certificate by the buyer; this certificate guarantees the binding relationship between them. One trusted third party acts as a lightweight notary for evidence generation. One advantage of this agent-based non-repudiation protocol is to reduce inconvenience for mobile clients such as connection time; it causes difficulty for fair transaction for mobile payments.

Optimal 3GPP packet-switched streaming service (PSS) over GPRS networks

3GPP packet-switched streaming service (PSS) is a standardized packet-based mobile streaming service, which is based on IETF RTSP/SDP standards. PSS can be implemented over GPRS networks; however these cannot usually guarantee any data rates or delay bounds, but allow sufficient bandwidth for mobile streaming. GPRS cell reselections pose additional challenges for streaming, since several seconds of data transmission breaks may occur, and data may even be lost. The level of error protection of GPRS is good enough for mobile streaming, if the correct quality of service (QoS) profile is configured. In this paper, we study the effect of different QoS parameters configurations to find optimal values for PSS over GPRS. The paper shows also a method for optimizing cell reselection management at the application layer, in order to provide seamless mobility. Results show that despite all the limitations of a GPRS environment, PSS is feasible with a decent quality of service.

Caching collaboration and cache allocation in peer-to-peer video systems

Providing scalable video services in a peer-to-peer (P2P) environment is challenging. Since videos are typically large and require high communication bandwidth for delivery, many peers may be unwilling to cache them in whole to serve others. In this paper, we address two fundamental research problems in providing scalable P2P video services: (1) how a host can find enough video pieces, which may scatter among the whole system, to assemble a complete video; and (2) given a limited buffer size, what part of a video a host should cache and what existing data should be expunged to make necessary space. We address these problems with two new ideas: Cell caching collaboration and Controlled Inverse Proportional (CIP) cache allocation. The Cell concept allows cost-effective caching collaboration in a fully distributed environment and can dramatically reduce video lookup cost. On the other hand, CIP cache allocation challenges the conventional caching wisdom by caching unpopular videos in higher priority. Our approach allows the system to retain many copies of popular videos to avoid creating hot spots and at the same time, prevent unpopular videos from being quickly evicted from the system. We have implemented a Gnutella-like simulation network and use it as a testbed to evaluate the proposed technique. Our extensive study shows convincingly the performance advantage of the new scheme.

A GA-based movie-on-demand platform using multiple distributed servers

In this paper we present the design and explore the performance of a unicast-based distributed system for Movie-on-Demand applications. The operation of multiple servers is coordinated with the assistance of an analytical framework that provides closed-form solutions to the content partitioning and scheduling problem, even under the presence of packet losses. The problem of mapping clients to servers is solved with a genetic algorithm, that manages to provide adequate, near-optimum solutions with a minimum of overhead. While previous studies focused on the static behavior of such a system, i.e. fixed a-priori known number of N servers and K clients commencing operation at the same time instance, this paper focuses on the dynamic behavior of such a system over a period of time with clients coming and going at random intervals. The paper includes a rigorous simulation study that shows how the system behaves in terms of a variety of metrics, including the average access time over all the requested media, in response to differences in the client arrival rate or the consumed server bandwidth. As it is shown, the proposed platform exhibits excellent performance characteristics that surpass traditional approaches that treat clients individually. This has been verified to be true up to extreme system loads, proving the scalability of the proposed content delivery scheme. The significance of our findings also stems from the assumption of unreliable communications, a first for the study of complete systems in this domain.

Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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Adaptive training of video sets for image recognition on mobile phones

We present an enhancement towards adaptive video training for PhoneGuide, a digital museum guidance system for ordinary camera-equipped mobile phones. It enables museum visitors to identify exhibits by capturing photos of them. In this article, a combined solution of object recognition and pervasive tracking is extended to a client–server-system for improving data acquisition and for supporting scale-invariant object recognition. A static as well as a dynamic training technique are presented that preprocess the collected object data differently and apply two types of neural networks (NN) for classification. Furthermore, the system enables a temporal adaptation for ensuring a continuous data acquisition to improve the recognition rate over time. A formal field experiment reveals current recognition rates and indicates the practicability of both methods under realistic conditions in a museum.

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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.