Proxy Caching Research Articles

Design and Evaluation of a Proxy Cache for Peer-to-Peer Traffic

Peer-to-peer (P2P) systems generate a major fraction of the current Internet traffic, and they significantly increase the load on ISP networks and the cost of running and connecting customer networks (e.g., universities and companies) to the Internet. To mitigate these negative impacts, many previous works in the literature have proposed caching of P2P traffic, but very few (if any) have considered designing a caching system to actually do it. This paper demonstrates that caching P2P traffic is more complex than caching other Internet traffic, and it needs several new algorithms and storage systems. Then, the paper presents the design and evaluation of a complete, running, proxy cache for P2P traffic, called pCache. pCache transparently intercepts and serves traffic from different P2P systems. A new storage system is proposed and implemented in pCache. This storage system is optimized for storing P2P traffic, and it is shown to outperform other storage systems. In addition, a new algorithm to infer the information required to store and serve P2P traffic by the cache is proposed. Furthermore, extensive experiments to evaluate all aspects of pCache using actual implementation and real P2P traffic are presented.

INTELLIGENT WEB CACHING USING MACHINE LEARNING METHODS

Web caching is a technology to improve network tra-c on the Internet. It is a temporary storage of Web objects for later retrieval. Three signiflcant ad- vantages of Web caching include reduction in bandwidth consumption, server load, and latency. These advantages make the Web to be less expensive yet it provides better performance. This research aims to introduce an advanced machine learning method for a classiflcation problem in Web caching that requires a decision to cache or not to cache Web objects in a proxy cache server. The challenges in this clas- siflcation problem include the issues in identifying attributes ranking and improve the classiflcation accuracy signiflcantly. This research includes four methods that are Classiflcation and Regression Trees (CART), Multivariate Adaptive Regression Splines (MARS), Random Forest (RF) and TreeNet (TN) for classiflcation on Web caching. The experimental results reveal that CART performed extremely well in classifying Web objects from the existing log data with a size of Web objects as a signiflcant attribute for Web cache performance enhancement.

Web Proxy Cache Content Classification based on Support Vector Machine

Web Proxy Cache Content Classification based on Support Vector Machine

Smallest Cache Utility Algorithm Based on Popularity

Streaming media is an important research direction in internet applications. In this paper, A Smallest Cache Utility algorithm based on Popularity in future (SCU-PK) is proposed. It comprehensively considered the merit of media time popularity and the smallest cache utility algorithm, using the entire file byte usefulness instead of the file segment bytes usefulness, so that a more effective byte usefulness calculation method and a more rational file segment popularity calculation method was designed and implement. The experiments show that the SCU-PK algorithm has better performance in increasing cache space utilization rate and byte hit ratio than LRU, LFU and SCU-PFUT in stream media proxy cache.

PopCap: popularity oriented proxy caching for peer-assisted Internet video-on-demand streaming services

With the success of Internet video-on-demand (VoD) streaming services, the bandwidth required and the financial cost incurred by the host of the video server becoming extremely large. Peer-to-peer (P2P) networks and proxies are two common ways for reducing the server workload. In this paper, we consider a peer-assisted Internet VoD system with proxies deployed at domain gateways. We formally present the video caching problem with the objectives of reducing the video server workload and avoiding inter-domain traffic, and we obtain its optimal solution. Inspired by theoretical analysis, we develop a practical protocol named PopCap for Internet VoD services. Compared with previous work, PopCap does not require additional infrastructure support, is inexpensive, and able to cope well with the characteristic workloads of Internet VoD services. From simulation-based experiments driven by real-world data sets from YouTube, we find that PopCap can effectively reduce the video server workload, therefore provides a superior performance regarding the video server's traffic reduction.

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.

Fuzzy Filtering-Based Segment Grouping for User-Centered Multimedia Streaming Service in P2P Distribution Mobile Networks

Segment-based proxy caching schemes are recently proposed to provide direct services of required media objects from the proxy without the help of media servers in P2P distribution mobile networks. These segment-based schemes, however, have such problems as jitter latency, congestion, interference, and re-transmission due to large data size, startup latency, and continuous synchronization of media objects. Thus this paper proposes a new FFSG (Fuzzy Filtering-based Segment Grouping) scheme for user-centered media streaming services to solve problems. The proposed scheme manages media objects in segments of FPRB (Fixed Partition Reference Block) or VPRB (Variable Partition Reference Block). Media objects are grouped as blocks of same fixed size in FPRB and as blocks of variable size in VPRB. The proposed scheme used semantic relationship for the grouping of divided media objects and used fuzzy relevance to filter out less relevant segments. The simulation result showed the improvements in average response ratio, cache hit ratio, startup latency rate, and service quality of streaming service.

A novel server-side proxy caching strategy for large-scale multimedia applications

Nowadays, server-side Web caching becomes an important technique used to reduce the User Perceived Latency (UPL). In large-scale multimedia systems, there are many Web proxies, connected with a multimedia server, that can cache some most popular multimedia objects and respond to the requests for them. Multimedia objects have some particular characteristic, e.g., strict QoS requirements. Hence, even some efficient conventional caching strategies based on cache hit ratio, meant for non-multimedia objects, will confront some problems in dealing with the multimedia objects. If we consider additional resources of proxy besides cache space, say bandwidth, we can readily observe that high hit ratios may deteriorate the entire system performance. In this paper, we propose a novel placement model for networked multimedia systems, referred to as the H k / T model, which considers the combined influence of arrival rate, size, and playback time to select the objects to be cached. Based on this model, we propose an innovative Web caching algorithm, named as the ART-Greedy algorithm, which can balance the load among the proxies and achieve a minimum Average Response Time (ART) of the requests. Our experimental results conclusively demonstrate that the ART-Greedy algorithm outperforms the most popular and commonly used LFU (Least Frequently Used) algorithm significantly, and can achieve a better performance than the byte-hit algorithm when the system utilization is medium and high.

On the Benefits of Cooperative Proxy Caching for Peer-to-Peer Traffic

This paper analyzes the potential of cooperative proxy caching for peer-to-peer (P2P) traffic as a means to ease the burden imposed by P2P traffic on Internet Service Providers (ISPs). In particular, we propose two models for cooperative caching of P2P traffic. The first model enables cooperation among caches that belong to different autonomous systems (ASs), while the second considers cooperation among caches deployed within the same AS. We analyze the potential gain of cooperative caching in these two models. To perform this analysis, we conduct an eight-month measurement study on a popular P2P system to collect traffic traces for multiple caches. Then, we perform extensive trace-based simulations to analyze different angles of cooperative caching schemes. Our results demonstrate that: 1) significant improvement in byte hit rate can be achieved using cooperative caching, 2) simple object replacement policies are sufficient to achieve that gain, and 3) the overhead imposed by cooperative caching is negligible. In addition, we develop an analytic model to assess the gain from cooperative caching in different settings. The model accounts for number of caches, salient P2P traffic features, and network characteristics. Our model confirms that substantial gains from cooperative caching are attainable under wide ranges of traffic and network characteristics.

Performance impact of large file transfer on web proxy caching: A case study in a high bandwidth campus network environment

Since large objects consume substantial resources, web proxy caching incurs a fundamental trade-off between performance (i.e., hit-ratio and latency) and overhead (i.e., resource usage), in terms of caching and relaying large objects to users. This paper investigates how and to what extent the current dedicated-server based web proxy caching scheme is affected by large file transfers in a high bandwidth campus network environment. We use a series of trace-based performance analyses and profiling of various resource components in our experimental squid proxy cache server. Large file transfers often overwhelm our cache server. This causes a bottleneck in a web network, by saturating the network bandwidth of the cache server. Due to the requests for large objects, response times required for delivery of concurrently requested small objects increase, by a factor as high as a few million, in the worst cases. We argue that this cache bandwidth bottleneck problem is due to the fundamental limitations of the current centralized web proxy caching model that scales poorly when there are a limited amount of dedicated resources. This is a serious threat to the viability of the current web proxy caching model, particularly in a high bandwidth access network, since it leads to sporadic disconnections of the downstream access network from the global web network. We propose a peer-to-peer cooperative web caching scheme to address the cache bandwidth bottleneck problem. We show that it performs the task of caching and delivery of large objects in an efficient and cost-effective manner, without generating significant overheads for participating peers.

Performance Impact of Large File Transfer on Web Proxy Caching: A Case Study in a High Bandwidth Campus Network Environment

Performance Impact of Large File Transfer on Web Proxy Caching: A Case Study in a High Bandwidth Campus Network Environment

Proxy‐assisted P2P and multicast transmission schemes for layered‐video streaming over wireless networks

AbstractThis work describes the process of efficiently streaming a set of layered‐videos from a remote server via proxy of the base station to multiple heterogeneous and asynchronous clients in wireless networks, such as the WiMAX network, which are devices that request different layers of the video according to their profiles. The process focuses on that the transmission cost savings for caching X layers of a video are not only from requests on X layers, but also from requests on layers that are lower than X layers. A set of proxy‐assisted transmission schemes are proposed for layered‐video streaming by integrating the proxy caching with reactive transmission schemes, peer‐to‐peer mesh networks and base station multicast capability. The optimal proxy prefix cache allocation is calculated for each transmission scheme to identify the cache layer and cache length of each video to minimize the aggregate transmission cost. Experimental results demonstrate that an adaptive proxy‐assisted transmission scheme can lead to significant transmission cost savings. Copyright © 2009 John Wiley & Sons, Ltd.

Proxy caching for peer-to-peer live streaming

Peer-to-Peer (P2P) live streaming has become increasingly popular over the Internet. To alleviate the inter-ISP traffic load and to minimize the access latency, proxy caching has been widely suggested for P2P applications. In this paper, we carry out an extensive measurement study on the properties of P2P live streaming data requests. Our measurement demonstrates that the P2P living streaming traffic exhibits strong localities that could be explored by caching. This is particularly noticeable for the temporal locality, which is often much weaker in the conventional P2P file sharing applications. Our results further suggest that the request time of the same data piece from different peers exhibits a generalized extreme value distribution. We then propose a novel sliding window (SLW)-based caching algorithm, which predicts and caches popular data pieces according to the measured distribution. Our experimental results suggest that the P2P live streaming can greatly benefit from the proxy caching. And, with much lower overhead, our SLW algorithm works closer to an off-line optimal algorithm that holds the complete knowledge of future requests.

A Dynamic Scheduling Algorithm for Mobile Streaming Media Based on Proxy Caching

A novel dynamic scheduling algorithm DS2AM2PC(Dynamic Scheduling Algorithm for Mobile Streaming Media based on Proxy Caching)for mobile streaming media based on proxy caching is proposed.It employs the scheme that the cache window size can be increased or decreased adaptively according to the popularity of the requested object and the patch bytes that are segmented and cached.Every time the segment patch with different or same number of bytes is cached at the proxy cache according to the different circumstances.The cache window size is updated periodically according to the popularity of mobile streaming media object.The maximum cache size is decided dynamically.The principle is obeyed that the data cached for each mobile streaming media object are in proportion to their popularity at the proxy server.Simulation results show that this strategy is more adaptive than P3S2A(Proxy-assisted Patch Pre-fetching and Service Scheduling Algorithm)algorithm and OBP(Optimized Batch Patching)+prefixpatch caching algorithm for the variety of the request arrival rates.It can significantly reduce patching data through patching channel under the circumstance of the same maximum cache space.This can effectively reduce the server load and network bandwidth usage on backbone link.It can faster cache the media object than P3S2A algorithm.It reduces the average occupied cache space at the proxy.

Proxy Caching for Video-on-Demand Using Flexible Starting Point Selection

In this paper, we propose a novel proxy caching scheme for video-on-demand (VoD) services. Our approach is based on the observation that streaming video users searching for some specific content or scene pay most attention to the initial delay, while a small shift of the starting point is acceptable. We present results from subjective VoD tests that relate waiting time and starting point deviation to user satisfaction. Based on this relationship as well as the dynamically changing popularity of video segments, we propose an efficient segment-based caching algorithm, which maximizes the user satisfaction by trading off between the initial delay and the deviation of starting point. Our caching scheme supports interactive video cassette recorder (VCR) functionalities and enables cache replacement with a much finer granularity compared to previously proposed segment-based approaches. Our experimental results show a significantly improved user satisfaction for our scheme compared to conventional caching schemes.

A Survey on Applications of Neural Networks and Evolutionary Techniques in Web Caching

Web caching has been used extensively to enhance content delivery to the clients by minimizing client-observed latency, reducing network bandwidth usage and improving scalability of the network. Caching performance can be improved by designing good replacement policies, prefetching techniques, clustering of web users and proper placement of proxy caches in the network. In this paper, we discuss the various approaches that were designed based on neural networks, genetic algorithms and fuzzy logic to optimize the performance of web caching. The approaches discussed here proved to be more effective in solving the problems as compared to the conventional techniques that were used earlier in this problem domain. Neural networks and evolutionary algorithms can be considered for further exploration in the various issues related to web caching and content delivery.

Quality-Adaptive Proxy Caching for Peer-to-Peer Video Streaming Using Multiple Description Coding

In the past few years, video streaming has been one of the most prominent applications in the Internet. There are basically two types of approaches to deliver on-demand video streams: infrastructure-based and infrastructure-less. The infrastructure-based approach, also known as the content delivery network (CDN) approach, employs numerous replicate servers and proxies to assist video streaming. The main drawback of this approach is that it is costly to deploy numerous servers and proxies. The infrastructure-less approach, also known as the peer-to-peer (P2P) approach, employs numerous peers to relay video streams. The main drawback of the P2P approach is its instability due to frequent joining/leaving of peers. The state-of-the-art development is to combine the two types of approaches. In this paper, we employ multiple description coding (MDC) to develop a novel P2P-assisted proxy caching scheme, called MP3, for on-demand video streaming. Our simulation results show that with the use of MDC, MP3 can effectively provide adaptive video quality for clients in a heterogeneous network environment.

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.

분산 멀티미디어 스트리밍 서비스를 위한 분할과 사상에 의한 프록시 캐싱 그룹화

최근에 분산 환경에서 서버를 거치지 않고 사용자가 요구하는 미디어 객체를 프록시로부터 직접 서비스하기 위한 동적 프록시 캐싱 기법이 제안되고 있다. 그러나 이러한 기법들은 멀티미디어 데이터 크기, 지연시간, 연속적인 미디어 객체 서비스 요구 등으로 인하여 여러 문제점들이 제기되고 있다. 본 논문에서는 이러한 문제를 해결하기 위하여 분할과 사상기반의 퍼지필터링에 의한 캐싱 그룹화 기법을 제안하였다. 분할과 사상을 위해 미디어 블록세그먼트를 고정분할 참조블록(RfP)와 가변분할 참조블록(RvP)로 구분하였으며, 시멘틱 관계성을 위해 고정분할 시간동기화(Tf)와 가변분할 시간동기화(Tv)에 의해 퍼지 관계성이 수행되도록 하였다. 시뮬레이션 결과 제안된 기법이 평균 요청응답률과 캐시 히트율을 증가시키고 시간지연율을 줄이며 스트리밍 서비스를 효율적으로 수행하게 됨을 알 수 있다. Recently, dynamic proxy caching has been proposed on the distributed environment so that media objects by user's requests can be served directly from the proxy without contacting the server. However, it makes caching challenging due to multimedia large sizes, low latency and continuous streaming demands of media objects. To solve the problems caused by streaming demands of media objects, this paper has been proposed the grouping scheme with fuzzy filtering based on partition and mapping. For partition and mapping, this paper divides media block segments into fixed partition reference block(R<TEX>$_f$</TEX>P) and variable partition reference block(R<TEX>$_v$</TEX>P). For semantic relationship, it makes fuzzy relationship to performs according to the fixed partition temporal synchronization(T<TEX>$_f$</TEX>) and variable partition temporal synchronization(T<TEX>$_v$</TEX>). Simulation results show that the proposed scheme makes streaming service efficiently with a high average request response time rate and cache hit rate and with a low delayed startup ratio compared with other schemes.

Traffic Modeling and Proportional Partial Caching for Peer-to-Peer Systems

Peer-to-peer (P2P) file sharing systems generate a major portion of the Internet traffic, and this portion is expected to increase in the future. We explore the potential of deploying proxy caches in different autonomous systems (ASes) with the goal of reducing the cost incurred by Internet service providers and alleviating the load on the Internet backbone. We conduct an eight-month measurement study to analyze the P2P traffic characteristics that are relevant to caching, such as object popularity, popularity dynamics, and object size. Our study shows that the popularity of P2P objects can be modeled by a Mandelbrot-Zipf distribution, and that several workloads exist in P2P traffic. Guided by our findings, we develop a novel caching algorithm for P2P traffic that is based on object segmentation, and proportional partial admission and eviction of objects. Our trace-based simulations show that with a relatively small cache size, a byte hit rate of up to 35% can be achieved by our algorithm, which is close to the byte hit rate achieved by an off-line optimal algorithm with complete knowledge of future requests. Our results also show that our algorithm achieves a byte hit rate that is at least 40% more, and at most triple, the byte hit rate of the common Web caching algorithms. Furthermore, our algorithm is robust in face of aborted downloads, which is a common case in P2P systems.