Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Memetic algorithms: a short introduction
New ideas in optimization
Tabu Search
View selection using randomized search
Data & Knowledge Engineering
On solving the view selection problem in distributed data warehouse architectures
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
An Evolutionary Approach to the Selection and Allocation of Distributed Cubes
IDEAS '06 Proceedings of the 10th International Database Engineering and Applications Symposium
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OLAP systems depend heavily on the materialization of multidimensional structures to speed-up queries, whose appropriate selection constitutes the cube selection problem. However, the recently proposed distribution of OLAP structures emerges to answer new globalization's requirements, capturing the known advantages of distributed databases. But this hardens the search for solutions, especially due to the inherent heterogeneity, imposing an extra characteristic of the algorithm that must be used: adaptability. Here the emerging concept known as hyper-heuristic can be a solution. In fact, having an algorithm where several (meta-)heuristics may be selected under the control of a heuristic has an intrinsic adaptive behavior. This paper presents a hyper-heuristic polymorphic algorithm used to solve the extended cube selection and allocation problem generated in M-OLAP architectures.