Distributed query processing plans generation using genetic algorithm


Large amount of information available in distributed databases needs to be exploited by organizations in order to be competitive in the market. In order to exploit this information, queries are posed thereupon. These queries require efficient processing, which mandates devising of optimal query processing strategies that generate efficient query processing plans for a given distributed query. The number of possible query processing plans grows rapidly with increase in the number of sites used, and relations accessed, by the query. There is a need to generate efficient query processing plans from among all possible query plans. The proposed approach attempts to generate such query processing plans using genetic algorithm. The approach generates query plans based on the closeness of data required to answer the user query. The query plans having the required data residing in fewer sites, are considered more efficient, and are thus preferred, over query plans having data spread across a large number of sites. The query plans so generated involve minimum number of sites for answering the user query leading to efficient query processing. Further, experimental results show that the GA based approach converges quickly towards the optimal query processing plans for an observed crossover and mutation rate. Read More

Publication: International Journal of Computer Theory and Engineering

Publisher: ResearchGate

Authors: T.V. Vijay Kumar, Vikram Singh, Ajay Kumar Verma

Keywords: Distributed Query Processing, Genetic Algorithm, Query Processing

Meet one of the Author:

Dr Ajay Kumar Verma completed his Ph.D. in Deep Learning based Meta-analysis of Gene Expression Data from Jawaharlal Nehru University, Delhi India. His background in Machine Learning, Deep Learning, NLP, Computer Vision, Computational Biology and Bioinformatics, Medical Imaging and Medical Informatics sets him apart from others and makes him a highly qualified expert in these fields.

Dr. Ajay Kumar Verma


Jawaharlal Nehru University, New Delhi, India – School of Computational and Integrative Sciences, carries out teaching and research in the inter-disciplinary areas of computational genomics, bioinformatics & drug discovery, database management & systems biology, high performance computing and artificial intelligence. The school’s academic and research programs are currently focused on the core area of computational and systems biology with future emphasis on the study of complex systems, high density data analysis, theoretical biophysical chemistry, and computational neurosciences.

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