Replicated Static Allocation of Fragments in Distributed Database Design using Biogeography- based Optimization

Allocation of data is one of the key design issues of distributed database. A major cost of query execution in a distributed database system is the data transfer cost from one site to another site. The allocation of fragments among the different sites over the network plays an important role in performance of the distributed database system. The main objective of a data allocation in distributed database is to place the data fragments at different sites in such a way, so that the total data transfer cost can be minimized while executing a set of queries. As data allocation in distributed database is NP-hard problem and therefore optimal solutions cannot be found in reasonable amount of time even for moderate size problems. Therefore it requires meta-heuristics algorithms to generate good solution in quick time. In this paper, a new algorithm has been proposed for replicated fragment allocation during distributed database design for static environment using biogeography-based optimization (BBO). The main objective of this paper is to design a replicated fragments allocation algorithm to minimize the total data transmission cost and storage cost of fragments. To show the performance of proposed algorithm, results of biogeography-based optimization algorithm for data allocation are compared with genetic algorithm.