Distributed databases principles and systems
Distributed databases principles and systems
ACM Computing Surveys (CSUR)
A state transition model for distributed query processing
ACM Transactions on Database Systems (TODS)
Query optimization by simulated annealing
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Randomized algorithms for optimizing large join queries
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A threshold mechanism for distributed query processing
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Query processing utilizing dependencies and horizontal decomposition
SIGMOD '83 Proceedings of the 1983 ACM SIGMOD international conference on Management of data
Query processing for distributed databases using generalized semi-joins
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
Performance Issues in Distributed Query Processing
IEEE Transactions on Parallel and Distributed Systems
A Heuristic Approach to Distributed Query Processing
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Genetic algorithms for large join query optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Optimal Query Processing for Distributed Database Systems
IEEE Transactions on Computers
Query Processing in Distributed Database System
IEEE Transactions on Software Engineering
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Query Processing is a key determinant in the overall performance of distributed databases. It requires processing of data at their respective sites and transmission of the same between them. These together constitute a distributed query processing strategy (DQP). DQP aims to arrive at an efficient query processing strategy for a given query. This strategy involves generation of efficient query plans for a distributed query. In case of distributed relational queries, the number of possible query plans grows exponentially with an increase in the number of relations accessed by the query. This number increases further when the relations, accessed by the query, have replicas at different sites. Such a large search space renders it infeasible to find optimal query plans. This paper presents a query plan generation algorithm that attempts to generate optimal query plans, for a given query, using genetic algorithm. The query plans so generated involve fewer sites, thus leading to efficient query processing. Further, experimental results show that the proposed algorithm converges quickly towards optimal query plans for an observed crossover and mutation probability.