Abstract
Most of the dynamic query optimization methods proposed in the literature are centralized. This centralization, in a large-scale environment, generates a bottleneck due to relatively important message exchange on a network with a weak bandwidth and strong latency. It becomes thus convenient to render autonomous and self-adaptable the query execution on a large-scale network. In this perspective, we propose a mobile relational algebra to decentralize the control of dynamic query optimization processes. Experiments, in local and large-scale distributed environments, allow: (i) to validate the proposed proactive migration policy, and (ii) to identify the efficiency intervals of proposed mobile relational algebra.