Caching is considered widely as an efficient way to reduce access latency and network bandwidth consumption. En-route caching, where caches are associated with routing nodes in the network, is proposed in the context of Web cache to exploit fully the potential of caching. To make sensible replacement and placement decision for en-route caching, traditional caching schemes either engage computation-intensive algorithm like dynamic programming or suffer from inferior performance in terms of average access latency. In this article, we propose a new caching scheme with cost-based replacement and random placement, which is named CRRP. The cost-based replacement of CRRP introduces probing request to timely perceive cost change and the random placement is independent of current caching state, of O(1) computational complexity of placement decision. Through extensive simulations, we show that CRRP outperforms a wide range of caching schemes and is very close to the traditional dynamic-programming-based algorithm, in terms of average access delay.

While web proxy caching is a widely deployed technique, the performance of a proxy cache is limited by the local storage. Some studies have addressed this limitation by using the residual resources of clients via a p2p method and have achieved a very high hit rate. However, these approaches treat web objects as homogeneous objects and there is no consideration of various web characteristics. Consequently, the byte hit rate of the system is limited, external bandwidth is wasted, and perceived user latency is increased. The present paper suggests an efficient p2p based web caching technique that manages objects with different policies so as to exploit the characteristics of web objects, such as size and temporal locality. Small objects are stored alone whereas large objects are stored by dividing them into numerous small blocks, which are distributed in clients. On a proxy cache, header blocks of large objects take the place of objects themselves and smaller objects are cached. This technique increases the hit rate. Unlike a web cache, which evicts large objects as soon as possible in the case where clients fulfill the role of backup storage, large objects are given higher priority than small objects in the proposed approach. This maximizes the effect of hits for large objects and thereby increases the byte hit rate. Furthermore, we construct simple latency models for various p2p based web caching systems and analyze the effects of the proposed policies on these systems. We then examine the performances of the efficient policies via a trace driven simulation. The results demonstrate that the proposed techniques effectively enhance web cache performance, including hit rate, byte hit rate, and response time.

The performance of en-route web caching mainly depends on where the caches are located and how the cache contents are managed. In this paper, we address the problem of proxy placement in en-route web caching for tree networks, i.e., computing the optimal locations for placing k web proxies in a network such that some specified objectives are achieved. Based on our proposed model, we formulate this problem as an optimization problem and compute the optimal locations using a computationally efficient dynamic programming-based algorithm. We also extend our solution for tree networks to solve the same problem for autonomous systems. Finally, we implement our algorithms and evaluate our model on several performance metrics through extensive simulation experiments. We also compare the performance of our model with the best available heuristic KMPC model, as well as the random proxy placement model. The implementation results show that our model outperforms all the other models with respect to all performance metrics considered. The average improvements of our model over the KMPC model and the random proxy placement model are about 31.9 percent and 58.6 percent in terms of all the performance metrics considered.

Peer-to-peer (P2P) web caching has been studied recently as it can exploit local caches of peers for web caching without additional infrastructure. However, dynamic join/leave behaviors or local caching strategies of the peers due to their autonomy in a P2P network may limit the performance of P2P web caching. To overcome these limitations, we propose an effective directory-based P2P web caching system under dynamic participation of peers. We introduce the object lifetime in a P2P network considering the lifetimes of both an object in the local cache of a peer and a peer who owns the object, and utilize this object lifetime information for neighbor selection and storage management in the P2P web caching framework. For the neighbor selection, the proposed system utilizes the object lifetimes in selecting accurately a neighbor who would still retain the requested object and still remain in the P2P network. To improve the storage management, the proposed system uses efficiently the entire cache storage of the P2P network in such a way that the object is stored selectively in the local cache of the peer who requested it, considering the object lifetime. The trace-driven simulation results show that the proposed system has higher accuracy and fewer redirection failures than the conventional directory-based P2P web caching system in the feasible P2P network.

Proxy caches have been used for a very long time to enhance the performance of web access. Along with the recent development of CDN (Content Distribution Network), the web proxy caching has also been adopted in many main techniques. This paper presents a new viewpoint on the possible improvement to the cooperative proxy caching, which can reduce outbound traffic and therefore ideally result in better response time. We take notice to the regional total cost of cache objects for optimizing content distribution. By contrast to the regular removal policies based on single proxy server, we prefer to evaluate a retrieved web object based on the metrics gathered from multiply proxy caches regionally. We particularly introduce a concept called post-removal analysis, which is used in measuring the value of the removed objects. Finally, we use the real proxy cache Squid to implement our proposal and modify the well-known cache benchmarking tool Web Polygraph to test this cooperative prototype. The test results prove that the proposed scheme can bring noticeable improvement on the performance of proxy caching.

Many cooperated web cache systems and protocols have been proposed. These systems, however, require expensive resources, such as external bandwidth and CPU power or storage of a proxy, while inducing hefty administrative costs to achieve adequate client population growth. Moreover, a scalability problem in the cache server management still exists. This paper suggests peer-to-peer client-clustering. The client-cluster provides a proxy cache with backup storage which is comprised of the residual resources of the clients. We use DHT based peer-to-peer lookup protocol to manage the client-cluster. With the natural characteristics of this protocol, the client-cluster is self-organizing, fault-tolerant, well-balanced and scalable. Additionally, we propose the Backward ICP which is used to communicate between the proxy cache and the client-cluster, to reduce the overhead of the object replication and to use the resources more efficiently. We examine the performance of the client-cluster via a trace driven simulation and demonstrate effective enhancement of the proxy cache performance.

With the advance of high-speed network technologies, availability and popularity of streaming media contents over the Internet has grown rapidly in recent years. Because of their distinct statistical properties and user viewing patterns, traditional delivery and caching schemes for normal web objects such as HTML files or images can not be efficiently applied to streaming media such as audio and video. In this paper, we therefore propose an integrated caching scheme for streaming media with segment-based caching and hierarchically distributed proxies. Firstly, each stream is divided into segments and their caching algorithms are considered to determine how to distribute the segments into different level proxies efficiently. Secondly, by introducing two kinds of segment priorities, segment replacing algorithms are proposed to determine which stream and which segments should be replaced when the cache is full. Finally, a Web-friendly caching scheme is proposed to integrate the streaming caching with the conventional caching of normal web objects. Performance of the proposed algorithms is verified by carrying out simulations.