Improving the Performances of JMS-Based Applications

In the Java world, a standardized interface exists for message-based middleware (MOMs): Java Messaging Service or JMS. And like other middleware, some JMS implementations use clustering techniques to provide some level of performance and fault-tolerance. In this paper, we analyse the efficiency of various clustering policy in a real-life cluster and the key parameters im-pacting the performances of MOMs. We show that the resource-efficiency of the clustering meth-ods can be very poor due to local instabilities and/or global load variations. To solve these issues, we describe the rules that control these parameters for optimal performances and we propose a solution based on autonomic computing to (i) dynamically adapt the load distribution among the servers (load-balancing aspect) and (ii) dynamically adapt the replication level (provisioning aspect). We present an evaluation that shows the impact of these rules on the performances and the behavior of dynamically provisioned clustered queue