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Replication is a commonly proposed solution to problems of scale associated with distributed services. However, when a service is replicated, each client must be assigned a server. Prior work has generally assumed the assignment to be static. In contrast, we propose a dynamic server selection, and show that it enables application-level congestion avoidance. Using tools to measure the available bandwidth and round trip latency (RTT), we demonstrate the dynamic server selection and compare it to previous static approaches. We show that because of the variability of paths in the Internet, dynamic server selection consistently outperforms static policies, reducing response times by as much as 50%. However, we also must adopt a systems perspective and consider the impact of the measurement method on the network. Therefore, we look at alternative low-cost approximations and find that the careful measurements provided by our tools can be closely approximated by much lighter-weight measurements. We propose a protocol using this method which is limited to at most a 1% increase in network traffic but which often costs much less in practice.
Carter et al. (Sat,) studied this question.