Mobile agent cooperation methods for large scale distributed dynamic query optimization

In this paper, we study the contribution of the execution model based on mobile agents to the distributed dynamic query optimization. We propose three cooperation methods allowing to the agents, reacting to the estimation errors, to move during the runtime. The performance evaluation shows the superiority of one of these methods. It is more powerful than a standard execution starting from 30% of estimation error and has a relatively small overhead compared to a standard execution when the estimation error is small.