A nested genetic algorithm for distributed database design

Distributed database design is a difficult and complex process involving two major, interrelated problems. First, data must be allocated to nodes in the network. Second given such an allocation data must be efficiently accessed, processed, and possibly communicated to meet the retrieval and update requirements of the users. Both of these problems can be formulated as constrained, integer, optimization problems; both of which are NP-hard. Genetic algorithms provide an efficient search method for problems of this type. We present a nested genetic algorithm that iteratively allocates data to nodes and determines where to perform access and processing operations to efficiently meet a specified set of retrieval and update requirements.<>