The World Wide Web can be considered as a large distributed information system that provides access to shared data objects. As one of the most popular applications currently running on the Internet, the World Wide Web is of an exponential growth in size, which results in network congestion and server overloading. Web caching has been recognized as one of the effective schemes to alleviate the service bottleneck and reduce the network traffic, thereby minimize the user access latency. In this paper, we first describe the elements of a Web caching system and its desirable properties. Then, we survey the state-of-art techniques which have been used in Web caching systems. Finally, we discuss the research frontier

This study seeks to understand how network failures affect the availability of service delivery across wide area networks and to evaluate classes of techniques for improving end-to-end service availability. Using several large-scale connectivity traces, we develop a model of network unavailability that includes key parameters such as failure location and failure duration. We then use trace-based simulation to evaluate several classes of techniques for coping with network unavailability. We find that caching alone is seldom effective at insulating services from failures but that the combination of mobile extension code and prefetching can improve average unavailability by as much as an order of magnitude for classes of service whose semantics support disconnected operation. We find that routing-based techniques may provide significant improvements, but that the improvements of many individual techniques are limited because they do not address all significant categories of network failures. By combining the techniques we examine, some systems may be able to reduce average unavailability by as much as one or two orders of magnitude.

Abstract We develop approximation algorithms for the problem of placing replicated data in arbitrary net-works, where the nodes may both issue requests for data objects and have capacity for storing data objects, so as to minimize the average data-access cost. We introduce the data placement problem tomodel this problem. We have a set of caches F, a set of clients D, and a set of data objects O. Each cache i can store at most ui data objects. Each client j 2 D has demand dj for a specific data object o(j) 2 O and has to be assigned to a cache that stores that object. Storing an object o in cache i incurs astorage cost of f oi, and assigning client j to cache i incurs an access cost of djcij. The goal is to find aplacement of the data objects to caches respecting the capacity constraints, and an assignment of clients

Consider a hierarchical network in which each node periodically issues a request for an object drawn from a fixed set of unit-size objects. Suppose further that the following conditions are satisfied: the frequency with which each node accesses each object is known; each node has a cache of known capacity; any cache can be accessed by any node; any request is satisfied by the closest node with a copy of the desired object, at a cost proportional to the distance between the accessing node and the closest copy. In such an environment, it is desirable to fill the available cache space with copies of objects in such a way that the average access cost is minimized. We provide both exact and approximate polynomial-time algorithms for this hierarchical placement problem. Our exact algorithm is based on a reduction to min-cost flow, and does not appear to be practical for large problem sizes. Thus we are motivated to search for a faster approximation algorithm. Our main result is a simple constant-factor approximation algorithm for the hierarchical placement problem that admits an efficient distributed implementation.

We present NPS, a novel non-intrusive web prefetching system that (1) utilizes only spare resources to avoid interference between prefetch and demand requests at the server as well as in the network , and (2) is deployable without any modifications to servers, browsers, network or the HTTP protocol. NPS's self-tuning architecture eliminates the need for traditional "thresholds" or magic numbers typically used to limit interference caused by prefetching, thereby allowing applications to improve bene ts and reduce the risk of aggressive prefetching.

In this paper, we examine the bandwidth-constrained placement problem, focusing on trade-os appropriate for wide area network (WAN) environments. The goal is to place copies of objects at a collection of distributed caches to minimize expected access times from distributed clients to those objects subject to a maximum bandwidth constraint at each cache. We develop a simple algorithm to generate a bandwidth-constrained placement by hierarchically rening an initial per-cache greedy placement. We prove that this hierarchical algorithm generates a placement whose expected access time is within a constant factor of the optimal placement's expected access time. We then proceed to extend this algorithm to compute close to optimal placement strategies for dynamic environments.

The rapid growth of time-critical information services and business-oriented applications is making quality of service (QoS) support increasingly important in content distribution. This paper investigates the problem of placing object replicas (e.g., web pages and images) to meet the QoS requirements of clients with the objective of minimizing the replication cost. We consider two classes of service models: replica-aware service and replica-blind service. In the replica-aware model, the servers are aware of the locations of replicas and can therefore direct requests to the nearest replica. We show that the QoS-aware placement problem for replica-aware services is NP-complete. Several heuristic algorithms for efficient computation of suboptimal solutions are proposed and experimentally evaluated. In the replica-blind model, the servers are not aware of the locations of replicas or even their existence. As a result, each replica only serves the requests flowing through it under some given routing strategy. We show that there exist polynomial optimal solutions to the QoS-aware placement problem for replicablind services. Efficient algorithms are proposed to compute the optimal locations of replicas under different cost models.

Internet evolves and operates largely without a central coordination, the lack of which was and is critically important to the rapid growth and evolution of Internet. However, the lack of management in turn makes it very difficult to guarantee proper performance and to deal systematically with performance problems. Meanwhile, the available network bandwidth and server capacity continue to be overwhelmed by the skyrocketing Internet utilization and the accelerating growth of bandwidth intensive content. As a result, Internet service quality perceived by customers is largely unpredictable and unsatisfactory. Content Distribution Network (CDN) is an e ective approach to improve Internet service quality. CDN replicates the content from the place of origin to the replica servers scattered over the Internet and serves a request from a replica server close to where the request originates. In this paper, we first give an overview about CDN. We then present the critical issues involved in designing and implementing an effective CDN and survey the approaches proposed in literature to address these problems. An example of CDN is described to show how a real commercial CDN operates. After this, we present a scheme that provides fast service location for peer-to-peer systems, a special type of CDN with no infrastructure support. We conclude with a brief projection about CDN.

Web caching has emerged as one solution for improving client latency on the web. Cache effectiveness depends on the policies used to route requests to other caches and servers, maintain up-to-date web objects (HTML files, images, etc.) and remove objects from the cache. Traditional caches apply the same policies to all web objects; however caches lack the ability to apply specialized policies to a subset of cached objects. We present an extensible caching infrastructure in which cache administrators, servers, and end users can customize how web objects are cached, replaced, and kept consistent. This paper presents a domain-specific programming language, CacheL, for defining customizable caching policies. The resulting infrastructure will lead to the development of a more efficient and customizable web caching solution.

This paper aims at finding fundamental design principles for hierarchical web caching. An analytical modeling technique is developed to characterize an uncooperative twolevel hierarchical caching system where the least recently used (LRU) algorithm is locally run at each cache. With this modeling technique, we are able to identify a characteristic time for each cache, which plays a fundamental role in understanding the caching processes. In particular, a cache can be viewed roughly as a low-pass filter with its cutoff frequency equal to the inverse of the characteristic time. Documents with access frequencies lower than this cutoff frequency have good chances to pass through the cache without cache hits. This viewpoint enables us to take any branch of the cache tree as a tandem of low-pass filters at different cutoff frequencies, which further results in the finding of two fundamental design principles. Finally, to demonstrate how to use the principles to guide the caching algorithm design, we propose a cooperative hierarchical web caching architecture based on these principles. Both model-based and real trace simulation studies show that the proposed cooperative architecture results in more than 50% memory saving and substantial central processing unit (CPU) power saving for the management and update of cache entries compared with the traditional uncooperative hierarchical caching architecture.