Recovery Strategies for Streaming Media Service in a Cluster-Based VOD Server with a Fault Node

Due to the economic cost and good scalability, cluster-based server architecture is used for VOD services. This server consists of a front-end node and multiple backend nodes. In this server architecture, backend nodes are added simply to support large-scale on-demand clients. However, as the number of backend nodes increases, the possibility of backend node failure also increases. A backend node fault not only degrades the quality of serviced streaming media but also decreases the number of streams supported in the VOD server. For successful VOD service, even if a backend node enters a fault state, the streaming service in progress should be re-continued after a short recovery time. As the recovery strategy, when legacy RAID methods are applied to cluster-based VOD servers, the excessive internal network traffic between the backend nodes causes performance degradation. In addition, the backend nodes demonstrate inefficient CPU utilization for the recovery process. In this paper, to address these problems, a new fault recovery strategy is proposed based on the pipeline computing concept. The proposed method not only distributes the network traffic generated from the recovery operations but also makes efficient use of the CPU time available in the backend nodes. Based on these advantages, even if the cluster-based server has a backend node that fails, the proposed method provides more QoS streams compared to the existing recovery method. In addition, since the proposed method needs a very short recovery time, the streaming services in progress are sustained without degradation of media quality.     

Parallel failure recovery techniques in cluster-based media servers

For large-scale video-on-demand (VOD) service, cluster servers are highlighted due to their high performance and low cost. A cluster server consists of a front-end node and multiple backend nodes. Though the increase in backend nodes provides more quality of service (QoS) streams, the possibility of backend node failure is proportionally increased. The failure causes not only the cessation of streaming services but also the loss of current playing positions. In this paper, when a backend node fails, recovery mechanisms are studied to support the streaming service continuously. Without considering the characteristics of cluster-based servers and MPEG media, the basic redundant array of independent disks (RAID) techniques cause a network bottleneck in the internal network path and demonstrate inefficient CPU usage in backend nodes. To address these problems, a new failure recovery mechanism is proposed based on the pipeline computing concept. The proposed method not only distributes the internal network traffic generated from the recovery operations but also utilizes the CPU time available in the backend nodes. In the experiments, even if a backend node fails, the proposed method provides continuous streaming media services within a short MTTR value as well as more QoS streams than the existing method.     

改进的分布式编码转换服务器负荷分担方法

针对当大量移动客户端需要流媒体服务时,编码转换服务器之间的负荷分担方法会较大地影响到总的满足服务质量（QoS）的流的数目的问题,提出了一种新的基于编码转换服务器资源消耗加权的负荷分担方法,用于均衡分布式编码转换服务器间的负荷,能使分布式编码转换服务器的性能得到更多的扩展。实验中,通过增加编码转换服务器的数目,评估了该方法均衡负荷的优越性和可扩展性。     

QoS-adaptive bandwidth scheduling in continuous media streaming

In this paper, we present a QoS-adaptive admission control and resource scheduling framework for continuous media (CM) servers. The framework consists of two parts. One is a reserve-based admission control mechanism in which new streams, arriving during periods of congestion, are offered lower QoS, instead of being blocked. The other part is a scheduler for continuous media with dynamic resource allocation to achieve higher utilization than non-dynamic schedulers by effectively sharing available resources among contending streams and by reclamation which is a scheduler-initiated negotiation to reallocate resources among streams to improve overall QoS. This soft-QoS framework recognizes that CM applications can generally tolerate certain variations on QoS parameters; that is, it exploits the findings about human tolerance to degradation in quality of multimedia streams. Using our policy, we could increase the number of simultaneously running clients that could be supported and could ensure a good response ratio and better resource utilization under heavy traffic requirements. Our admission control and scheduling strategy provides three principle advantages over conventional mechanisms. First, it guarantees better total system utilization. Second, it provides better disk utilization and larger admission ratio for input CM streams, which is a major advantage. Third, it still presents acceptable play-out qualities compared to the conventional greedy admission control algorithm.     

Replication and retrieval strategies for resource-effective admission control in multi-resolution video servers

Video-on-demand (VOD) service requires balanced use of system resources, such as disk bandwidth and buffer, to accommodate more clients. The data retrieval size and data rates of video streams directly affect the utilization of these resources. Given the data rates which vary widely in multi-resolution video servers, we need to determine the appropriate data retrieval size to balance the buffer with the disk bandwidth. Otherwise, the server may be unable to admit new clients even though one of the resources is available for use. To address this problem, we propose the following new schemes that work together: (1) A replication scheme called Splitting Striping units by Replication (SSR). To increase the number of admitted clients, SSR defines two sizes of striping unit, which allow data to be stored on the primary and backup copies in different ways. (2) A retrieval scheduling method which combines the merits of existing SCAN and grouped sweeping scheme (GSS) algorithms to balance the buffer and disk bandwidth usage. (3) Admission control algorithms which decide whether to read data from the primary or the backup copy. The effectiveness of the proposed schemes is demonstrated through simulations. Results show that our schemes are able to cope with various workloads efficiently and thus enable the server to admit a much larger number of clients.     

基于协作缓存的视频点播系统中调度设计

随着计算机技术和网络技术的不断进步,视频点播服务已经逐渐变成现实,基于协作缓存的视频点播系统是一个分布式结构,中心集群存放影片数据,本地集群缓存数据并提供视频点播服务,具有很好的可扩展性。该文针对VOD系统的协作缓存,提出了静态调度和动态迁移相结合的调度策略,静态调度能够根据影片数据的缓存分布情况,实时调度服务请求,并同时考虑多个VOD服务器的负载动态平衡;动态任务迁移能对服务流分布进行实时分析,并根据服务数据本地化的原则进行服务迁移,进一步提高了协作缓存的命中率。该文阐述了基于协作缓存的视频点播系统的拓扑结构,对静态调度和动态迁移进行了详细设计,并给出了相应的形式化表示。     

移动边缘计算中资源受限的动态服务部署策略

移动边缘计算（MEC）的出现使移动用户能够以低延迟访问部署在边缘服务器上的服务。然而,MEC仍然存在各种挑战,尤其是服务部署问题。边缘服务器的数量和资源通常是有限的,只能部署数量有限的服务;此外,用户的移动性改变了不同服务在不同地区的流行度。在这种情况下,为动态请求部署合适的服务就成为一个关键问题。针对该问题,通过了解动态用户请求来部署适当的服务以最小化交互延迟,将服务部署问题表述为一个全局优化问题,并提出了一种基于集群划分的资源聚合算法,从而在计算、带宽等资源约束下初步部署合适的服务。此外,考虑动态用户请求对服务流行度及边缘服务器负载的影响,开发了动态调整算法来更新现有服务,以确保服务质量（QoS）始终满足用户期望。通过一系列仿真实验验证了所提出策略的性能。仿真结果表明,与现有基准算法相比,所提出的策略可以降低服务交互延迟并实现更稳定的负载均衡。     

QoS-Aware Admission Control and Dynamic Resource Provisioning Framework in Ubiquitous Multimedia Computing Environments

A ubiquitous service deployment is emerging in the multimedia, networking, and wireless mobile computing area. Therefore, there has been an increasing demand for ubiquitous computing environments to support a certain degree of quality of service (QoS) to meet various service requirements from different computing and networking applications, and to better utilize the computing resources. However, supporting QoS in the ubiquitous computing environments has also raised great concerns regarding the applicability of any QoS solution. Management of such ubiquitous multimedia applications requires new mechanisms, i.e., Soft-QoS framework, to be developed for admission control, negotiation, allocation, and scheduling. In this paper, we present a novel negotiated admission control algorithm that exploits the degradability property of applications to improve the performance of the system. The algorithm is based on setting aside a portion of the resources as reserves and managing it intelligently, so that the total utility of the system can be maximized. The mixed greedy and predictive strategy leads to an efficient protocol that also improves the system performance. We use the constructs of application benefit functions and resource demand functions in the integrated admission control and negotiation protocol. We applied our Soft-QoS framework to the admission controlling and resource scheduling for ubiquitous multimedia devices such as Continuous Media (CM) or Video-On-Demand (VOD) servers, where multimedia applications can generally tolerate certain variations on QoS parameters by providing multiple classes with consistently proportional rather than absolute QoS. Extensive simulation experiments are presented in the paper to evaluate the performance of the novel mechanisms and compare it against some other methods used in the past.This work was in part funded by DARPA through the SPAWARSYSCEN under Contract Number N66001-97-C-8525 and SK Telecom, Korea, under Contract Number (KU-R0405721).     

QCWS: an implementation of QoS-capable multimedia web services

QoS (Quality of Service), which defines service quality such as latency, availability, timeliness and reliability, is important for web applications that provide real-time information, multimedia content, or time-critical services. Many web applications are best implemented by servers with a guaranteed server processing capacity. In this research, we study the QoS control issues using the current Web services standards. We propose a QoS-capable Web service architecture, QCWS, by deploying a QoS broker between Web service clients and providers. The functions of the QoS broker module include tracking QoS information about servers, making selection decisions for clients, and negotiating with servers to get QoS agreements. We have implemented a QCWS prototype using IBM WSDK, enhanced with simple QoS capabilities. We have measured the performance running under different service priorities.     

Efficient support for interactive service in multi-resolution VOD systems

Advances in high-speed networks and multimedia technologies have made it feasible to provide video-on-demand (VOD) services to users. However, it is still a challenging task to design a cost-effective VOD system that can support a large number of clients (who may have different quality of service (QoS) requirements) and, at the same time, provide different types of VCR functionalities. Although it has been recognized that VCR operations are important functionalities in providing VOD service, techniques proposed in the past for providing VCR operations may require additional system resources, such as extra disk I/O, additional buffer space, as well as network bandwidth. In this paper, we consider the design of a VOD storage server that has the following features: (1) provision of different levels of display resolutions to users who have different QoS requirements, (2) provision of different types of VCR functionalities, such as fast forward and rewind, without imposing additional demand on the system buffer space, I/O bandwidth, and network bandwidth, and (3) guarantees of the load-balancing property across all disks during normal and VCR display periods. The above-mentioned features are especially important because they simplify the design of the buffer space, I/O, and network resource allocation policies of the VOD storage system. The load-balancing property also ensures that no single disk will be the bottleneck of the system. In this paper, we propose data block placement, admission control, and I/O-scheduling algorithms, as well as determine the corresponding buffer space requirements of the proposed VOD storage system. We show that the proposed VOD system can provide VCR and multi-resolution services to the viewing clients and at the same time maintain the load-balancing property. Received June 9, 1998 / Accepted April 26, 1999     

Video placement and configuration of distributed video servers on cable TV networks

A large-scale, distributed video-on-demand (VOD) system allows geographically dispersed residential and business users to access video services, such as movies and other multimedia programs or documents on demand from video servers on a high-speed network. In this paper, we first demonstrate through analysis and simulation the need for a hierarchical architecture for the VOD distribution network.We then assume a hierarchical architecture, which fits the existing tree topology used in today's cable TV (CATV) hybrid fiber/coaxial (HFC) distribution networks. We develop a model for the video program placement, configuration, and performance evaluation of such systems. Our approach takes into account the user behavior, the fact that the user requests are transmitted over a shared channel before reaching the video server containing the requested program, the fact that the input/output (I/O) capacity of the video servers is the costlier resource, and finally the communication cost. In addition, our model employs batching of user requests at the video servers. We study the effect of batching on the performance of the video servers and on the quality of service (QoS) delivered to the user, and we contribute dynamic batching policies which improve server utilization, user QoS, and lower the servers' cost. The evaluation is based on an extensive analytical and simulation study.     

An analytical approach to providing controllable differentiated quality of service in Web servers

Provisioning quality of service (QoS) in Web servers has gained immense importance because Web servers are a major part of the Internet. To deliver the pledged QoS, Web service providers need control over the allocation of the resources in their Web servers. Control is also necessary for reaching the optimal resource allocation through proper service differentiation. In this paper, we propose and investigate an analytic approach that enables the service providers to deploy a differentiated service policy that offers this control. The proposed service policy is configurable by tunable control parameters. We devise the relationships between the performance measures and these parameters by adopting a unique queuing theoretic approach. Once these relationships are established, we describe how these parameters can be set to their most appropriate values depending on the objectives of the service providers. We illustrate the usefulness of our approach by conducting the analysis on a real Web trace.     

Buffer-Sharing Techniques in Service-Guaranteed Video Servers

Advances in networking and storage technology have made it possible to deliver on-demand services over networks such as the emerging video-on- demand (VOD) applications. Although a variety of studies have been focused on designing video servers suitable for VOD applications, the number of concurrent on-demand services supported by such servers is often limited by the I/O bandwidth of the storage systems. Recently, several researchers have focused on providing guaranteed services instead of on-demand services in a VOD system. A service is said to be guaranteed if every viewer can be served within a specified waiting time after the video has been subscribed. This paper describes a model called a buffer-sharing autonomy, which combines batching and bridging techniques to provide guaranteed services to VOD systems. We also describe how buffer-sharing techniques can be used in this model to provide the same services with fewer buffer resource through the use of playback-rate alteration. Additionally, in order to make buffer sharing efficient, it is important to group appropriate video streams together to share buffer resource. Four grouping policies are proposed for this purpose and the benefits yielded are also analyzed and compared. Finally, the results of our experiments show that the proposed buffer-sharing techniques promise the provision of guaranteed video services at low cost.     

支持QoS的操作系统框架的研究

视频会议、VOD、数字图书馆等实时多媒体应用要求计算机系统的资源管理者-操作系统必须支持QoS。该文提出了一种支持QoS的操作系统框架,该框架包括了资源的静态管理和动态管理策略,支持QoS需求到资源需求的转换、映射,支持允许控制、资源预留、动态调度与维护机制。文章对支持QoS所需的几个关键子系统进行了深入的研究,包括满足QoS需求的CPU调度算法、存储管理策略、磁盘I/O调度方法和网络接口的控制。     

Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

An analytical model for interval caching in interactive video servers

Design of servers to meet the quality of service (QoS) requirements of interactive video-on-demand (VOD) systems is challenging. Recognizing the increasing use of these systems in a wide range of applications, as well as the stringent service demands expected from them, several design alternatives have been proposed to improve server throughput. A buffer management technique, called interval caching, is one such solution which exploits the temporal locality of requests to the same movie and tries to serve requests from the cache, thereby enhancing system throughput.In this paper, we present a comprehensive mathematical model for analyzing the performance of interactive video servers that use interval caching. The model takes into account the representative workload parameters of interactive servers employing interval caching and calculates the expected number of cached streams as an indication of the improvement in server capacity due to interval caching. Especially, user interactions, which sensitively affect the performance of interval caching, are realistically reflected in our model for an accurate analysis. A statistical admission control technique has also been developed based on this model. Using this model as a design tool, we apply the model to measure the impact of different VCR operations on client requests and rejection probability, as well as the effect of cache size.     

A novel resource allocation mechanism for live cloud-based video streaming service

With the recent emergence of cloud computing, growing numbers of clients are using online cloud services through the Internet such as video streaming service. The rent costs of cloud service providers increase when the resource utilizations of the cloud-servers are not well. Therefore, resource allocation is a crucial problem for cloud data centers. The resource allocation problem is an NP-hard problem. This paper proposes a novel cloud resource allocation mechanism based on a winning strategy for a Nim game. This mechanism offers all clients an effective number of running cloud servers, and allocates cloud resources rapidly and effectively by using a pre-pairing approach. The proposed mechanism does not require searching for remaining resources of the running cloud server; hence, it can reduce the time taken to arrange resources. The experimental results show that the proposed mechanism can improve utilization of cloud servers and reduce the rent costs of the cloud service providers. The proposed mechanism can reach the utilization of cloud servers by as much as 99.96 %. The proposed mechanism is approximately 9 % more efficient than the market-based grid resource allocation algorithm, and 19 % more efficient than the modified best fit decreasing algorithm.

     

Resource allocation optimization for quantitative service differentiation on server clusters

The goal of service differentiation is to provide different service quality levels to meet changing system configuration and resource availability and to satisfy different requirements and expectations of applications and users. In this paper, we investigate the problem of quantitative service differentiation on cluster-based delay-sensitive servers. The goal is to support a system-wide service quality optimization with respect to resource allocation on a computer system while provisioning proportionality fairness to clients. We first propose and promote a square-root proportional differentiation model. Interestingly, both popular delay factors, queueing delay and slowdown, are reciprocally proportional to the allocated resource usage. We formulate the problem of quantitative service differentiation as a generalized resource allocation optimization towards the minimization of system delay, defined as the sum of weighted delay of client requests. We prove that the optimization-based resource allocation scheme essentially provides square-root proportional service differentiation to clients. We then study the problem of service differentiation provisioning from an important relative performance metric, slowdown. We give a closed-form expression of the expected slowdown of a popular heavy-tailed workload model with respect to resource allocation on a server cluster. We design a two-tier resource management framework, which integrates a dispatcher-based node partitioning scheme and a server-based adaptive process allocation scheme. We evaluate the resource allocation framework with different models via extensive simulations. Results show that the square-root proportional model provides service differentiation at a minimum cost of system delay. The two-tier resource allocation framework can provide fine-grained and predictable service differentiation on cluster-based servers.     

A Tabu search approach for designing a non-hierarchical video-on-demand network architecture

In this paper, we present a tabu search to design a non-hierarchical and decentralized video-on-demand (VOD) network architecture. To optimize the VOD network resource, we consider optimization of both video server locations and storage allocation subject to the tradeoffs among installation cost for video servers, program storage cost, and transmission (or communication) cost. In applying a tabu search technique to the problem, neighborhood structure and search strategy are elaborated to improve solution quality and to reduce computation time. We report the results of the computational experiments to demonstrate the performance of the proposed tabu search. A comparative study shows that our algorithm is promising.     

CBC: Caching for cloud-based VOD systems

Cloud-based video on demand (VOD) service is a promising next-generation media streaming service paradigm. Being a resource-intensive application, how to maximize resource utilization is a key issue of designing such an application. Due to the special cloud-based VOD system architecture consisting of cloud storage cluster and media server cluster, existing techniques such as traditional caching strategies are inappropriate to be adopted by a cloud-based VOD system directly in practice. Therefore, in this study, we have proposed a systemic caching scheme, which seamlessly integrates a caching algorithm and a cache deployment algorithm together to maximize the resources utilization of cloud-based VOD system. Firstly, we have proposed a cloud-based caching algorithm. The algorithm models the cloud-based VOD system as a multi-constraint optimization problem, so as to balance the resource utilization between cloud storage cluster and media server cluster. Secondly, we have proposed a cache deployment algorithm. The algorithm further manages the bandwidth and cache space resource utilization inside the media server cluster in a more fine-grained manner, and achieves load balancing performance. Our evaluation results show that the proposed scheme enhances the resource utilization of the cloud-based VOD system under resource-constrained situation, and cuts down the reject ratio of user requests.