Characterization and Analysis of a Nested Genetic Algorithm for Distributed Database Design

Distributed database design is a difficult and complex task involving two interdependent problems: data allocation and operation allocation. First, data must be allocated to nodes in the network. Second, given such an allo-cation, data must be efficiently retrieved, processed, and possibly com-municated to meet the retrieval and update requirements of the users. The problem is characterized by integer variables, a discontinuous and extremely complex cost function, and numerous constraints. A nested genetic algorithm naturally fits this problem formulation with the outer algorithm addressing data allocation and the inner algorithm addressing operation allocation. We present and characterize such an algorithm according to its gene structure and control parameters. We experimentally analyze the effects of poolsize and crossover operator on the performance of our algorithm. Index Terms- Genetic algorithms, performance modeling and analysis, ex-perimental analysis of algorithms, distributed database desig