Server replication is an approach often used to improve the ability of a service to handle a large number of clients. One of the important factors in the efficient utilization of replicated servers is the ability to direct client requests to the best server, according to some optimality criteria. In this paper we target an environment in which servers are distributed across the Internet, and clients identify servers using our application-layer anycasting service. Our goal is to allocate servers to clients in a way that minimizes a client's response time. To that end, we develop an approach for estimating the performance that a client would experience when accessing particular servers. Such information is maintained in a resolver that clients can query to obtain the identity of the server with the best response time. Our performance collection technique combines server push with client probes to estimate the expected response time. A set of experiments is used to demonstrate the propert...

Abstract--Server replication improves the ability of a service to handle a large number of clients. One of the important fac-tors in the efficient utilization of replicated servers is the ability to direct client requests to the "best " server, according to some optimality criteria. In the anycasting communication paradigm, a sender communicates with a receiver chosen from an anycast group of equivalent receivers. As such, anycasting is well suited to the problem of directing clients to replicated servers. This paper examines the definition and support of the anycasting paradigm at the application layer, providing a service that uses an anycast resolver to map an anycast domain name and a selection criteria into an IP address. By realizing anycasting in the appli-cation layer, we achieve flexibility in the optimization criteria and ease the deployment of the service. As a case study, we examine the performance of our system for a key service: replicated web servers. To this end, we develop an approach for estimating the response time that a client will experi-ence when accessing given servers. Such information is maintained in the anycast resolver that clients query to obtain the identity of the server with the best estimated response time. Our performance collection technique combines server push with resolver probes to estimate the expected response time without undue overhead. Our experiments show that selecting a server using our architecture and estimation technique can improve the client response time by a factor of two over nearest server selection and by a factor of four over random server selection. Index Terms--Anycasting, replication, server selection. I.

The anycasting communication paradigm is designed to support server replication by allowing applications to easily select and communicate with the "best" server, according to some performance or policy criteria, in a group of content-equivalent servers. We examine the definition and support of the anycasting paradigm at the application layer, providing a service that maps anycast domain names into one or more IP addresses using anycast resolvers. In addition to being independent from network-layer support, our definition includes the notion of filters, functions that are applied to groups of addresses to affect the selection process. We consider both metric-based filters (e.g., server response time) and policy-based filters. An expanded version of this work can be found as a technical report. 1 . 1 Introduction The Internet is increasingly being viewed as providing services, and not just connectivity. As this view becomes more prevalent, it becomes important to provide, within the ...