Swarm intelligence in cube selection and allocation for multi-node OLAP systems

Abstract

The continuous growth of OLAP users and data impose additional stress on data management and hardware infrastructure. The distribution of multidimensional data through a number of servers allows the increasing of storage and processing power without an exponential increase of financial costs. But this solution adds another dimension to the problem: space. Even in centralized OLAP, cube selection efficiency is complex, but now, we must also know where to materialize subcubes. This paper proposes algorithms that solve the distributed OLAP selection problem under space constraints, considering a query profile, using discrete particle swarm optimization in its normal, cooperative, multi-phase and hybrid genetic versions.