Reducing bandwidth requirement for delivering video over wide area networks with proxy server

Due to the high bandwidth requirement and rate variability of compressed video, delivering video across wide area networks (WANs) is a challenging issue. Proxy servers have been used to reduce network congestion and improve client access time on the Internet by caching passing data. We investigate ways to store or stage partial video in proxy servers to reduce the network bandwidth requirement over WAN. A client needs to access a portion of the video from a proxy server over a local area network (LAN) and the rest from a central server across a WAN. Therefore, client buffer requirement and video synchronization are to be considered. We study the tradeoffs between client buffer, storage requirement on the proxy server, and bandwidth requirement over WAN. Given a video delivery rate for the WAN, we propose several frame staging selection algorithms to determine the video frames to be stored in the proxy server. A scheme called chunk algorithm, which partitions a video into different segments (chunks of frames) with alternating chunks stored in the proxy server, is shown to offer the best tradeoff. We also investigate an efficient way to utilize client buffer when the combination of video streams from WAN and LAN is considered.     

Frame Selection for Dynamic Caching Adjustment in Video Proxy Servers

By caching video data, a video proxy server close to the clients can be used to assist video delivery and alleviate the load of video servers. We assume a video can be partially cached and a certain number of video frames are stored in the proxy server. In our setting, the proxy server is allowed to cache the passing data from the video server. A video provides several options (levels) in terms of bandwidth requirement over the server-proxy path. For each video, the proxy server decides to cache a smaller amount of data at a lower level or to accumulate more data to reach a higher level. The proxy server can dynamically adjust the cached video data by choosing an appropriate level based on the network condition or the popularity of the video. We propose a frame selection scheme, Dynamic Chunk Algorithm, to determine which frames are to be cached in the proxy server for the dynamic caching adjustment scenario. The algorithm guarantees the rate constraint over the server-proxy path to be satisfied for each level. This approach also maintains the set of cached frames at a higher level as a superset of the cached frames at a lower level. Hence, it enforces the proxy server to simply cache more data without dropping frames when it intends to reduce network bandwidth consumption for a video and vice versa.     

Peer Assisted Video Streaming With Supply-Demand-Based Cache Optimization

In this paper, we consider a hybrid P2P video on-demand architecture that utilizes both the server and the peer resources for efficient transmission of popular videos. In our system architecture, each peer dedicates some cache space to store a particular segment of a video file as well as some of its upload bandwidth to serve the cached segment to other peers. Peers join the system and issue a streaming request to a control server. Control server directs the peers to streaming servers or to other peers who have the desired video segments. Control server also decides which peer should cache which video segment. Our main contribution in this paper is to determine the proper caching strategies at peers such that we minimize the average load on the streaming servers.      

A video caching policy for providing differentiated service grades and maximizing system revenue in hierarchical video servers

A video server normally targets at providing abundant bandwidth access and massive storage in supporting large-scale video archival applications. Its performance is sensitive to the deployment of the stored contents. In this paper, we propose a video caching policy for a video server, based on the knowledge of video profiles, namely: access rate, video size and bandwidth, tolerable rejection probability, and rental price. We consider the video server as having a hierarchical architecture which consists of a set of high-speed disk drives located in the front end for caching a subset of videos, and another set of high-capacity tertiary devices located in the back end for archiving the entire video collection. The front-end disks particularly, are organized together by employing a proposed data striping scheme, termed the adaptive striping (AS), which is flexible on heterogeneous disk integration. The proposed policy determines what video set should be cached, and how to arrange them in the front-end disks with two objectives in mind: (1) offering differentiated service grades conforming to the video profiles as well as (2) maximizing the overall system revenue. We simulate the system with various configurations, and the results affirm our effective approach.     

Robust wireless sharing of internet video streams

The gateways are the performance bottleneck of wireless mesh access networks and thus alleviating stress on them is essential to making such wireless networks robust and scalable. Using proxy servers or wireless peer-to-peer streaming techniques can help reduce the gateway load. However, these techniques, because they are data caching methods, do not save wireless resources. We instead consider a communication-sharing approach in this paper. Traditional stream sharing solutions depend on cooperation with the video server. However, in the wireless access network it is difficult to cooperate with online video sites. To address this problem in wireless mesh access networks, we propose a distributed video sharing technique called Dynamic Stream Merging (DSM). DSM is able to improve the robustness of the access network without cooperation from the online video site or the users and has the intelligence to handle sudden spikes in demand for certain videos due to specific events, thereby preventing adverse effects to other daily wireless traffic. The technique can also leverage the 80:20 data access pattern, common for many video applications, to substantially increase the service throughput. We explain the DSM technique, present the system prototype, and discuss the experimental results.     

A neural network proxy cache replacement strategy and its implementation in the Squid proxy server

As the Internet has become a more central aspect for information technology, so have concerns with supplying enough bandwidth and serving web requests to end users in an appropriate time frame. Web caching was introduced in the 1990s to help decrease network traffic, lessen user perceived lag, and reduce loads on origin servers by storing copies of web objects on servers closer to end users as opposed to forwarding all requests to the origin servers. Since web caches have limited space, web caches must effectively decide which objects are worth caching or replacing for other objects. This problem is known as cache replacement. We used neural networks to solve this problem and proposed the Neural Network Proxy Cache Replacement (NNPCR) method. The goal of this research is to implement NNPCR in a real environment like Squid proxy server. In order to do so, we propose an improved strategy of NNPCR referred to as NNPCR-2. We show how the improved model can be trained with up to twelve times more data and gain a 5–10% increase in Correct Classification Ratio (CCR) than NNPCR. We implemented NNPCR-2 in Squid proxy server and compared it with four other cache replacement strategies. In this paper, we use 84 times more data than NNPCR was tested against and present exhaustive test results for NNPCR-2 with different trace files and neural network structures. Our results demonstrate that NNPCR-2 made important, balanced decisions in relation to the hit rate and byte hit rate; the two performance metrics most commonly used to measure the performance of web proxy caches.     

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.

The Japan Cache Project: an experiment on domain cache

This paper proposes the concept of a domain cache, which is dedicated to handling access to a particular domain name, and reports experiments in the Japan Cache Project which operates a public cache server for access to JP (Japan) domain web servers. The goal of this project is to spread information about Japan to North America. This project included some experiments in prefetching information to makes use of less crowded access times, maintaining the coherence between the cache server and primary servers by primary server refresh, and operating a cache replication server, which keeps the primary server information in the cache and functions not as a proxy server but as an HTTP server.The high cache hit ratio obtained suggests that domain caching is an effective cache server operation method. However, we could not perform effective prefetching because of the difficulty in predicting user accesses. Coherence maintaining and cache replication server mechanisms were created. We appeal for cooperation from servers in Japan.     

Exploiting Regularities in Web Traffic Patterns for Cache Replacement

Abstract. Caching web pages at proxies and in web servers' memories can greatly enhance performance. Proxy caching is known to reduce network load and both proxy and server caching can significantly decrease latency. Web caching problems have different properties than traditional operating systems caching, and cache replacement can benefit by recognizing and exploiting these differences. We address two aspects of the predictability of traffic patterns: the overall load experienced by large proxy and web servers, and the distinct access patterns of individual pages. We formalize the notion of ``cache load' under various replacement policies, including LRU and LFU, and demonstrate that the trace of a large proxy server exhibits regular load. Predictable load allows for improved design, analysis, and experimental evaluation of replacement policies. We provide a simple and (near) optimal replacement policy when each page request has an associated distribution function on the next request time of the page. Without the predictable load assumption, no such online policy is possible and it is known that even obtaining an offline optimum is hard. For experiments, predictable load enables comparing and evaluating cache replacement policies using partial traces , containing requests made to only a subset of the pages. Our results are based on considering a simpler caching model which we call the interval caching model . We relate traditional and interval caching policies under predictable load, and derive (near)-optimal replacement policies from their optimal interval caching counterparts.     

一种Tracker引导的缓存调度方法

为优化流媒体视频点播系统中客户端对数据的缓存调度,使整个系统的播放质量与资源利用率趋向最优,提出一种Tracker引导的缓存调度方法,Tracker收集缓存服务器的负载信息和网络中的数据请求信息,采用基于流行度的预测方法推测下一阶段网络中需要的副本数,以此为根据对客户端缓存建议请求予以响应.客户端以Tracker的建议和自身在邻域网络内感知到的副本数为依据,使用兼顾全局和局部利益的决策算法进行视频数据的缓存操作.模拟结果表明,Tracker引导的缓存调度方法能够有效的保证网络中客户端节点的播放质量,并在一定程度上降低缓存服务器的负担,使整个系统的缓存调度趋向最优.     

基于后缀动态多缓存协作的流媒体分发技术

在Internet上高效传输流媒体数据是推广诸如视频点播等应用的基础．现有方案仅考虑了采用单代理结构的前缀缓存和服务器调度来降低骨干网带宽消耗和服务器负载．在带前缀缓存的Batch patching基础上提出了后缀的动态缓存算法ICBR，并提出了基于ICBR缓存算法的多缓存协作体系结构及协作算法MCC，仿真结果表明，基于ICBR的多缓存协作显著地降低了获取补丁而导致的骨干网带宽的消耗，提高了客户端QoS同时也降低了服务器负载．     

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.

Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.     

Tulip: A New Hash Based Cooperative Web Caching Architecture

With the exponential growth of WWW traffic, web proxy caching becomes a critical technique for Internet web services. Well-organized proxy caching systems with multiple servers can greatly reduce the user perceived latency and decrease the network bandwidth consumption. Thus, many research papers focused on improving web caching performance with the efficient coordination algorithms among multiple servers. Hash based algorithm is the most widely used server coordination mechanism, however, there's still a lot of technical issues need to be addressed. In this paper, we propose a new hash based web caching architecture, Tulip. Tulip aggregates web objects that are likely to be accessed together into object clusters and uses object clusters as the primary access units. Tulip extends the locality-based algorithm in UCFS to hash based web proxy systems and proposes a simple algorithm to reduce the data grouping overhead. It takes into consideration the access speed dispatch between memory and disk and replaces expensive small disk I/O with less large ones. In case a client request cannot be fulfilled by the server in the memory, the system fetches the whole cluster which contains the required object into memory, the future requests for other objects in the same cluster can be satisfied directly from memory and slow disk I/Os are avoided. It also introduces a simple and efficient data dupllication algorithm, few maintenance work need to be done in case of server join/leave or server failure. Along with the local caching strategy, Tulip achieves better fault tolerance and load balance capability with the minimal cost. Our simulation results show Tulip has better performance than previous approaches.     

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.     

集中管理式Web缓存系统及性能分析

共享缓存文件是减少网络通信量和服务器负载的重要方法，本文在介绍Web Caching技术及流行的Web缓存通信协议ICP的基础上，提出了一种集中管理式Web缓存系统，该系统通过将用户的HTTP请求，按照一定的算法分发到系统中某一合适的缓存服务器上，从而消除了缓存系统内部服务器之间庞大的通信开销及缓存处理负担，减少了缓存内容的冗余度．通过分析，证明了集中管理式Web缓存系统比基于ICP的简单缓存系统具有缓存效率高、处理开销低、延迟小等优点，并且该系统具有良好的可扩展性．     

一种基于分散协作的Web缓存集群体系结构

Web对象缓存技术是一种减少Web访问通信量和访问延迟的重要手段，该文通过分析现有的各种Web缓存系统，提出了一种基于分散协作的Web缓存集群体系结构。该体系结构克服了集中式系统需要额外配备一台管理服务器的缺陷，消除了管理服务器瓶颈失效造成系统瘫痪的危险，减少由于管理服务器带来的延迟；同时消除了分散系统的缓存不命中情况下的多级转发的延迟和缓存内容重叠，提高了资源利用率和系统效率，具有良好的可扩展性和健壮性。     

Lease-based consistency schemes in the web environment

There are many methods to maintain consistency in the distributed computing environment. Ideally, efficient schemes for maintaining consistency should take into account the following factors: lease duration of replicated data, data access pattern and system parameters. One method used to supply strong consistency in the web environment is the lease method. During the proxy’s lease time from a web server, the web server can notify the modification to the proxy by invalidation or update. In this paper, we analyze lease protocol performance by the varying update/invalidation scheme, lease duration and read rates. By using these analyses, we can choose the adaptive lease time and proper protocol (invalidation or update scheme of the modification for each proxy in the web environment). As the number of proxies for web caching increases exponentially, a more efficient method for maintaining consistency needs to be designed. We also present three-tier hierarchies on which each group and node independently and adaptively choose the proper lease time and protocol for each proxy cache. These classifications of the scheme make proxy caching adaptive to client access pattern and system parameters.     

一种新的基于代理缓存的流媒体分送策略

提出了一种新的带缓存的补丁调度策略,有效地将代理缓存与服务器调度技术结合起来,采用基于缓存窗口自适应伸缩的缓存分配方案,实现了流媒体对象在代理服务器中缓存的数据段数与其流行度成正比的原则。理论分析及实验结果表明,该策略有效地降低了服务器及骨干网络带宽资源的消耗,对于客户请求到达速率的变化具有非常好的适应性。     

基于网络性能的智能Web加速技术——缓存与预取

Web业务在网络业务中占有很大比重,在无法扩大网络带宽时,需要采取一定技术合理利用带宽,改善网络性能。研究了基于RTT（round trip time)等网络性能指标的Web智能加速技术,在对Web代理服务器上的业务进行分析和对网络RTT进行测量分析的基础上,提出了智能预取控制技术及新的缓存（cache）替换方法。对新算法的仿真研究表明,该方法提高了缓存的命中率。研究表明预取技术在不明显增加网络负荷的前提下,提高了业务的响应速度,有效地改进了Web访问性能。