Dynamic load-balancing using prediction in a parallel object-oriented system

In this paper, a replication-based parallel object model will be presented first, where object replication is used to improve the performance of load-balancing and to reduce the cost of object migration. After that, a threshold-based dynamic load-balancing strategy, that makes use of the object replication, will be introduced. The paper will then focus on a performance prediction model that is used in the decision making of the dynamic load-balancing strategy. The prediction model monitors the runtime behavior of an invoked method and estimates the execution time of its subsequent invocations. It helps the dynamic load-balancing strategy to make wiser decisions on whether or not to migrate objects in order to achieve better performance. A detailed simulation system is constructed to evaluate the performance of the proposed dynamic load-balancing strategy and the prediction model. Experimental results of the simulation will also be discussed in the paper.