Application-layer anycasting: a server selection architecture and use in a replicated Web service

• Published in: IEEE/ACM transactions on networking 2000-08, Vol.8 (4), p.455-466
• Main Authors: Zegura, E.W., Ammar, M.H., Zongming Fei, Bhattacharjee, S.
• Format: Article
• Language: English
• Subjects: Architecture; Clients; Computer science; Criteria; Delay; Estimating; Maintenance; Network servers; Probes; Quality of service; Receivers; Resolvers; Response time; Servers; Service oriented architecture; Studies; Web and internet services; Web server; Web services; Websites
• ISSN: 1063-6692; 1558-2566
• DOI: 10.1109/90.865074

Server replication improves 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 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 application-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 experience 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.