Self - monitoring for the horizontal fragmentation evolution based on ants in the Relational datawarehouses

In the context of relational data warehouses administration, the use of structures and techniques optimization is an issue to provide decision-making information within a reasonable time. The selection of such technical or structure scheme is NP-Complete problem. Researchers involved in this activity optimization often use approximate methods to reduce the complexity of the selection problem of these optimization techniques. Among these methods, we find, for example those based on genetic algorithm and ant colony. Through our research, we proposed a new method based on ants while exploiting their sorting behavior for resolving the selection problem of horizontal fragmentation. It consists to determine all the subsets of rows in the fact table that introduce the same predicates. These subsets are building the basis for partitioning the fact table. Our work has been the subject of an experiment on the benchmark APBl and gave very satisfactory results.