On the Optimal Placement of Web Proxies in the Internet: The Linear Topology

Abstract

Web caching or web proxy has been considered as the prime vehicle to cope with the ever-increasing demand for information retrieval over the Internet, WWW being a typical example. The existing work on web proxy has primarily focused on content based caching; relatively less attention has been given to the development of proper placement strategies for the potential web proxies in the Internet. This paper investigates the optimal placement policy of web proxies for a target web server in the Internet. The objective is to minimize the overall latency of searching the target web server subject to the network resources and traffic pattern. Specifically, we are interested in finding the optimal placement of multiple web proxies (m) among the potential sites (n) under a given traffic pattern. We model the problem as a Dynamic Programming problem, and we obtain an optimal solution for a linear array topology using O(n 2 m) time.

Comparison and analysis of ten static heuristics-based Internet data replication techniques

“…A majority of the initial work focused on coarse-grained replication. For example, the work proposed in [38] modeled the Internet as a tree. The work is also based on the assumption that the access requests to the proxies by the clients (which reside on the leaves of the tree) are always on the direct path(s) toward the servers.…”

“…The work is also based on the assumption that the access requests to the proxies by the clients (which reside on the leaves of the tree) are always on the direct path(s) toward the servers. The work reported in [38] deals with the proxy server placement. The heuristic approach proposed in [25] solves the replication problem without requiring the full knowledge of the network topology, which is commonly assumed in many approaches [42].…”

“…The heuristics approach was further improved in [26] by introducing a refined constrained based policy. A comprehensive comparison of replication algorithms using realistic data from Internet log files is done in [50], where the Greedy approach [50], outperforms the Dynamic Programming approach [38], Randomized [50], and Hot Spot [50]. Although replicating the entire contents of the website can reduce the hit-miss ratio by considerable amounts, the coarse-grained replication model is rather simplistic approach [42].…”

A Greedy Algorithm for Capacity-Constrained Surrogate Placement in CDNs

“…Previous studies typically formulate this decision problem as the minimum k-median problem [3,4], the facility location problem [3], the minimum k-center problem [5], or for simple network topologies (e.g., line, ring, or tree), the dynamic programming problem [3,[6][7][8][9].…”

“…All of these previous works [3][4][5][6][7][8][9], however, take a network-centric view of the issue of surrogate placement, assuming that a client's requests can always be directed to the surrogates closest to the client. Consequently, they consider only the network latency factor and the resultant placement scheme may very likely lead to an undesirable load concentration on some surrogates.…”