Access Time Minimization for Distributed Multimedia Applications

The problem of minimizing the access time of a requested multimedia (MM) document on a network based environment is addressed. A generalized version of this problem is formulated and retrieval strategies that minimize the access time of the user-requested MM document from a pool of MM servers are proposed. To this end, we design single-installment and multi-installment MM document retrieval strategies, through which the minimization of access time can be carried out. The main idea is to utilize more than one MM server in downloading the requested document. Each server assumes the responsibility of uploading a predetermined portion of the entire document in a particular order. Single- and multi-installment strategies differ in the number of disjoint document pieces each server sends to the client. We first introduce a directed flow graph (DFG) model to represent the retrieval process and generate a set of recursive equations using this DFG. Then, we derive closed-form solutions for the portions of the MM document downloaded from the various servers and the corresponding access time. We present rigorous analysis for these two strategies and show their performance under MPEG-I and MPEG-II video streams playback rates. Their behavior under different network bandwidths is also examined, revealing in-depth information about their expected performance. We also show that in the case of a multi-installment strategy, the access time can be completely controlled by fine tuning the number of installments. Since the number of installments is software tunable, the adaptive nature of the strategies to different channel bandwidths is also demonstrated. Important trade-off studies with respect to the number of servers involved in the retrieval process and the number of installments are presented. In the case of a heterogeneous network employing a single-installment strategy, we prove that the access time is independent of the server sequence used. Illustrative examples are provided for ease of understanding.     

Collaborative multi-step mono-level multi-strategy classification

In this paper, we address the problem of retrieving a movie from a set of multimedia(MM) servers by the clients on a network. We consider a strategy in which multiple MM servers are deployed by the service provider (SP) to retrieve a requested MM movie to the clients, for minimizing the access time (the waiting time of the client before initiating the playback) and maximizes the system reliability. We design a movie retrieval strategy that explicitly considers issues such as reliability and/or availability factors of the multimedia servers and the communication channels in the problem formulation. We develop a mathematical model for this retrieval strategy and derive an optimal size of each movie portion that is expected to be rendered by each server. We then derive a closed-form expression for the access time of the MM document and the system reliability which gives a trade-off relationship between access time and reliability (availability) of the service by our strategy. We extend our study to investigate on the effect of sequencing of the servers, the order in which movie portions are to be retrieved, to minimize the access time and to maximize the system reliability. With system reliability factors, we identify an optimal sequence, which maximizes system reliability out of all possible retrieval sequences. We then propose two methods to retrieve any missing movie portions upon a server failure during the retrieval process. In order to measure the quality of service provided by the service provider to its customers, we introduce a QoS parameter that can tune the playback rate to avoid any data underflow or overflow situations. Then, from probabilistic perspective, we obtain an estimate of the failure time of a single server and its resulting missing movie portion caused by this server failure. We conduct rigorous simulation experiments to testify all the theoretical findings reported. Illustrative examples are provided for the ease of understanding.     

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.     

An indexing scheme for energy-efficient processing of content-based retrieval queries on a wireless data stream

Wireless data broadcasting is a popular data delivery approach in mobile computing environments, where the broadcasting servers usually adopt indexing schemes for mobile clients to energy-efficiently access data on a wireless broadcast stream. However, conventional indexing schemes use primary key attribute values to construct tree structures. Therefore, these schemes do not support content-based retrieval queries such as partial-match queries and range-queries. This paper proposes an indexing method that supports content-based retrieval queries on a wireless data stream. The method uses a tree-structured index, called B2V-Tree, which is composed of bit-vectors that are generated from data records through multi-attribute hashing. Through analysis and experiments, the effectiveness of the proposed method is shown.     

Real-time broadcast algorithm for mobile computing

Broadcasting mechanisms have been widely used to transfer information to a large number of clients. Information is transferred by broadcast servers (satellites or base stations) downstream with a wide bandwidth. Most of the broadcast schemes try to minimize the average “access time”. This paper presents a real-time broadcast algorithm that transfers many information items including one with timing constraint. Our real-time broadcast algorithm attempts to meet the deadline for real-time information as well as to minimize the average access time for non-real-time information. Simulation results show that our algorithm can reduce the average access time for the non-real-time information while meeting the deadline for the real-time information.     

Application-Layer Protocol for Collaborative Multimedia Presentations

Many multimedia presentation applications involve retrieval of objects from more than one collaborating server. Presentations of objects from different collaborating servers might be interdependent. For instance, we can consider distributed video servers where blocks of movies are distributed over a set of servers. Here, blocks of a movie from different video servers have to be retrieved and presented continuously without any gaps in the presentation. Such applications first need an estimate of the available network resources to each of the collaborating server in order to identify a schedule for retrieving the objects composing the presentation. A collaborating server can suggest modifications of the retrieval schedule depending on its load. These modifications can potentially affect the retrieval schedule for other collaborating applications. Hence, a sequence of negotiations have to be carried out with the collaborating servers in order to commit for a retrieval schedule of the objects composing the multimedia presentation. In this paper, we propose an application sub-layer protocol, Resource Lock Commit Protocol (RLCP), for handling the negotiation and commitment of the resources required for a collaborative multimedia presentation application.     

A buffered-bandwidth approach for supporting real-time video streaming over cellular networks

In this paper, we study the admission and bandwidth allocation problems in real-time video streaming in a cellular network. Admission control in a cellular network is a complex issue due to the mobility of the clients, and the additional workload imposed by incoming clients could exceed the network capacity of a cell and seriously degrade the quality of services provided to the resident clients. To minimize the number of forced terminations of real-time video playback, we incorporate the notion of buffered bandwidth in the admission test for handoff client. Using this approach, we can balance the video workload among adjacent cells to minimize the impact of overloading as the result of handoff operations. We also examine techniques to maintain fairness in services especially under overload situations even though the requested videos from various types of clients could generate very different workload. Simulation experiments confirm the effectiveness of our approach compared to widely used schemes.     

Multiple-server movie-retrieval strategies for distributed multimedia applications: a play-while-retrieve approach

In this paper, we present a generalized approach to retrieve a long-duration movie requested using a network-based video-on-demand service infrastructure employing multiple servers. We design and analyze a play-while-retrieve (PWR) playback strategy for this multiserver environment such that the access time (waiting time for the clients) is minimized. For this strategy, we use both the single-installment and multi-installment retrieval strategies to analyze the performance of the service system. For the above-mentioned retrieval strategies, we explicitly derive closed-form expressions for a minimum access time. For the case of multi-installment retrieval strategy, we conduct asymptotic performance analysis that quantifies the ultimate performance bounds of our strategy. We demonstrate analytically the impact of a large-scale network, as well as the impact of indefinitely increasing the number of installments, on the performance of such a multiserver service system. We then address the problem of buffer management at the client site, which is a closely related issue that has a significant influence on the performance of the strategy, and also serves as a key issue in making the service system attractive for clients. We derive relationships that quantify the minimum amount of buffer expected at the client site to have a smooth presentation with this multiserver service structure. Finally, we perform simulation experiments to verify all our theoretical findings. In the experiments, we compare the performance of PWR strategy with that of play-after-retrieve strategy, and discuss certain important points that are crucial for implementing a real-life working multiserver service system.     

Random-accessible compressed triangle meshes

With the exponential growth in size of geometric data, it is becoming increasingly important to make effective use of multilevel caches, limited disk storage, and bandwidth. As a result, recent work in the visualization community has focused either on designing sequential access compression schemes or on producing cache-coherent layouts of (uncompressed) meshes for random access. Unfortunately combining these two strategies is challenging as they fundamentally assume conflicting modes of data access. In this paper, we propose a novel order-preserving compression method that supports transparent random access to compressed triangle meshes. Our decompression method selectively fetches from disk, decodes, and caches in memory requested parts of a mesh. We also provide a general mesh access API for seamless mesh traversal and incidence queries. While the method imposes no particular mesh layout, it is especially suitable for cache-oblivious layouts, which minimize the number of decompression I/O requests and provide high cache utilization during access to decompressed, in-memory portions of the mesh. Moreover, the transparency of our scheme enables improved performance without the need for application code changes. We achieve compression rates on the order of 20:1 and significantly improved I/O performance due to reduced data transfer. To demonstrate the benefits of our method, we implement two common applications as benchmarks. By using cache-oblivious layouts for the input models, we observe 2?6 times overall speedup compared to using uncompressed meshes.     

Presentation planning for distributed VoD systems

A distributed video-on-demand (VoD) system is one where a collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in distributed VoD systems, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present different types of presentation plans that a local server can construct in order to satisfy a customer request. Informally speaking, a presentation plan is a temporally synchronized sequence of steps that the local server must perform in order to present the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, while keeping within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, in order to evaluate the quality of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer and minimizing access bandwidth which, informally speaking, specifies how much network/disk bandwidth is used. We develop algorithms to compute three different optimal presentation plans that work at a block level, or at a segment level, or with a hybrid mix of the two, and compare their performance through simulation experiments. We have also mathematically proven effects of increased buffer or bandwidth and data replications for presentation plans which had previously been verified experimentally in the literature.     

Loopback: exploiting collaborative caches for large-scale streaming

In this paper, we propose a Loopback approach in a two-level streaming architecture to exploit collaborative client/proxy buffers for improving the quality and efficiency of large-scale streaming applications. At the upper level we use a content delivery network (CDN) to deliver video from a central server to proxy servers. At the lower level a proxy server delivers video with the help of collaborative client caches. In particular, a proxy server and its clients in a local domain cache different portions of a video and form delivery loops. In each loop, a single video stream originates at the proxy, passes through a number of clients, and finally is passed back to the proxy. As a result, with limited bandwidth and storage space contributed by collaborative clients, we are able to significantly reduce the required network bandwidth, I/O bandwidth, and cache space of a proxy. Furthermore, we develop a local repair scheme to address the client failure issue for enhancing service quality and eliminating most required repairing load at the central server. For popular videos, our local repair scheme is able to handle most of single-client failures without service disruption and retransmissions from the central server. Our analysis and simulations have shown the effectiveness of the proposed scheme.     

An Anticipative Recursively Adjusting Mechanism for parallel file transfer in data grids

Data Grids enable the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for content needed by large‐scale data‐intensive applications such as high‐energy physics, bioinformatics, and virtual astrophysical observatories. In Data Grids, co‐allocation architectures were developed to enable parallel downloads of data sets from selected replica servers. As Internet is usually the underlying network of a grid, network bandwidth plays as the main factor affecting file transfers between clients and servers. In this paradigm, there are still some challenges that need to be solved, such as to reduce differences in finish times between selected replica servers, to avoid traffic congestion resulting from transferring the same blocks in different links among servers and clients, and to manage network performance variations among parallel transfers. In this paper, we propose the Anticipative Recursively Adjusting Mechanism (ARAM) scheme to adjust the workloads on selected replica servers and handle unpredictable variations in network performance by those servers. Our algorithm is based on using the finish rates for previously assigned transfers to anticipate the bandwidth status for the next section to adjust workloads, and to reduce file transfer times in grid environments. Our approach is useful in grid environments with unstable network link. It not only reduces idle time wasted waiting for the slowest server, but also decreases file transfer completion times. Copyright © 2010 John Wiley & Sons, Ltd.     

Metropolitan area video-on-demand service using pyramid broadcasting

Pyramid broadcasting is a new way of giving video-on-demand service on a metropolitan scale. We multiplex the most frequently requested movies on the network, gaining a radical improvement in access time and bandwidth use. This is achieved by using storage at the receiving end. As the available bandwidth increases, the improvement in access time is exponential instead of linear as in conventional broadcasting. The larger the bandwidth of the network is, the better gain in the access time due to pyramid broadcasting. As the access-time requirement decreases, the bandwidth in conventional broadcasting increases linearly, while the bandwidth in pyramid broadcasting increases only logarithmically. We provide analytical and experimental evaluations of pyramid broadcasting based on its implementation on an Ethernet LAN.     

Exploiting data mining techniques for broadcasting data in mobile computing environments

Mobile computers can be equipped with wireless communication devices that enable users to access data services from any location. In wireless communication, the server-to-client (downlink) communication bandwidth is much higher than the client-to-server (uplink) communication bandwidth. This asymmetry makes the dissemination of data to client machines a desirable approach. However, dissemination of data by broadcasting may induce high access latency in case the number of broadcast data items is large. We propose two methods aiming to reduce client access latency of broadcast data. Our methods are based on analyzing the broadcast history (i.e., the chronological sequence of items that have been requested by clients) using data mining techniques. With the first method, the data items in the broadcast disk are organized in such a way that the items requested subsequently are placed close to each other. The second method focuses on improving the cache hit ratio to be able to decrease the access latency. It enables clients to prefetch the data from the broadcast disk based on the rules extracted from previous data request patterns. The proposed methods are implemented on a Web log to estimate their effectiveness. It is shown through performance experiments that the proposed rule-based methods are effective in improving the system performance in terms of the average latency as well as the cache hit ratio of mobile clients.     

Storage System for Supporting More Video Streams in Video Server

Video server needs a storage system with large bandwidth in order to provide concurrently more users with the real time retrieval requests for video streams. So, the storage system generally has the structure of disk array, which consists of multiple disks. When the storage system serves multiple video stream requests, it's bottlenecks come from the seeking delay caused by the random movement of disk head and from unbalanced disk access due to disk load unbalance among multiple disks.This paper presents a novel placement and retrieval policy. The new policy retrieves the requested data through sequential movement of disk heads and maintaining disk load balance so that it can diminish the bottlenecks on retrieving and can provide the concurrent real time retrieval services for more users simultaneously. In addition, the novel policy reduces the startup latency for the requests. The correctness of the novel placement and retrieval policy is analyzed with theoretical views. Performance analysis of the novel placement and retrieval policy is provided with simulations.     

Logically Clustered Architectures for Networked Databases

By effectively harnessing networked computing resources, the two-tier client-server model has been used to support shared data access. In systems based on this approach, the database servers often become performance bottlenecks when the number of concurrent users is large. Client data caching techniques have been proposed in order to ease resource contention at the servers. The key theme of these techniques is the exploitation of user data access locality. In this paper, we propose a three-tiered model that takes advantage of such data access locality to furnish a much more scalable system. Groups of clients that demonstrate similarities in their data access behavior are logically clustered together. Each such group of clients is handled by an Intermediate Cluster Manager (ICM) that acts as a cluster-wide directory service and cache manager. Clients within the same cluster are now capable of sharing data among themselves without interacting with the server(s). This results in reduced server load and allows the support of a much larger number of clients. Through prototyping and experimentation, we show that the logical clustering of clients, and the introduction of the ICM layer, significantly improve system scalability as well as transaction response times. Logical clusters, consisting of clients with similar data access patterns, are identified with the help of both a greedy algorithm and a genetic algorithm. For the latter, we have developed an encoding scheme and its corresponding operators.     

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.     

基于期限的多请求数据检索问题研究

给定一个包含多条信道的集合以及一个包含多个请求的集合,其中每一个请求包含多个请求数据项并且希望在一定期限内下载到,基于期限的多请求数据检索问题指当客户配有多条天线时寻找一个在期限内下载多个请求的数据检索序列,使得所有天线的最大访问延迟最小化。大多数现有数据检索方法关注于单个请求或者单条天线,很少研究当客户配有多条天线时多请求的数据检索问题,尤其是每一个请求的检索有时间约束。基于此,本文提出一种多请求的数据检索算法,以调度合适地天线检索这些请求并找到关于这些请求的检索序列,从而平衡在各天线上的访问延迟。针对单请求的数据检索,本文采用最大团思想寻找下载该请求中所有请求数据项的访问模式,使得检索该请求的访问延迟以及期限丢失率最小化。     

Load sharing in distributed multimedia-on-demand systems

Service providers have begun to offer multimedia-on-demand services to residential estates by installing isolated, small-scale multimedia servers at individual estates. Such an arrangement allows the service providers to operate without relying on a highspeed, large-capacity metropolitan area network, which is still not available in many countries. Unfortunately, installing isolated servers can incur very high server costs, as each server requires spare bandwidth to cope with fluctuations in user demand. The authors explore the feasibility of linking up several small multimedia servers to a (limited-capacity) network, and allowing servers with idle retrieval bandwidth to help out servers that are temporarily overloaded; the goal is to minimize the waiting time for service to begin. We identify four characteristics of load sharing in a distributed multimedia system that differentiate it from load balancing in a conventional distributed system. We then introduce a GWQ load sharing algorithm that fits and exploits these characteristics; it puts all servers' pending requests in a global queue, from which a server with idle capacity obtains additional jobs. The performance of the algorithm is captured by an analytical model, which we validate through simulations. Both the analytical and simulation models show that the algorithm vastly reduces wait times at the servers. The analytical model also provides guidelines for capacity planning. Finally, we propose an enhanced GWQ+L algorithm that allows a server to reclaim active local requests that are being serviced remotely. Simulation experiments indicate that the scheduling decisions of GWQ+L are optimal, i.e., it enables the distributed servers to approximate the performance of a large centralized server     

Using bundles for Web content delivery

The protocols used by the majority of Web transactions are HTTP/1.0 and HTTP/1.1. HTTP/1.0 is typically used with multiple concurrent connections between client and server during the process of Web page retrieval. This approach is inefficient because of the overhead of setting up and tearing down many TCP connections and because of the load imposed on servers and routers. HTTP/1.1 attempts to solve these problems through the use of persistent connections and pipelined requests, but there is inconsistent support for persistent connections, particularly with pipelining, from Web servers, user agents, and intermediaries. In addition, the use of persistent connections in HTTP/1.1 creates the problem of non-deterministic connection duration. Web browsers continue to open multiple concurrent TCP connections to the same server. This paper examines the idea of packaging the set of objects embedded on a Web page into a single bundle object for retrieval by clients. Based on measurements from popular Web sites and an implementation of the bundle mechanism, we show that if embedded objects on a Web page are delivered to clients as a single bundle, the response time experienced by clients is better than that provided by currently deployed mechanisms. Our results indicate that the use of bundles provides shorter overall download times and reduced average object delays as compared to HTTP/1.0 and HTTP/1.1. This approach also reduces the load on the network and servers. Implementation of the mechanism requires no changes to the HTTP protocol.