IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Replica refresh strategies in a database cluster
VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
Ordering vs timeliness: two facets of consistency?
Future directions in distributed computing
A generic and flexible model for replica consistency management
ICDCIT'04 Proceedings of the First international conference on Distributed Computing and Internet Technology
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One of the well-known challenges in using replication to service multiple clients concurrently is that of delivering a timely and consistent response to the clients. In this paper, we address thisproblem in the context of client applications that have specific temporal and consistency requirements. These applications can tolerate a certain degree of relaxed consistency, in exchange for better response time. We propose a flexible QoS model that allows these clients to specify their temporal and consistency constraints. In order to select replicas to serve these clients, we need to control the inconsistency of the replicas, so that we have a large enoughpool of replicas with the appropriate state to meet a client's timeliness, consistency, and dependability requirements. We describe an adaptive framework that uses lazy update propagation to control the replica inconsistency and employs a probabilistic approach toselect replicas dynamically to service a client, based on its QoS specification. The probabilistic approach predicts the ability of a replica to meet a client's QoS specification by using the performance history collected by monitoring the replicas at runtime. We conclude with experimental results based on our implementation.