Generating Distributed Query Processing Plans Using Genetic Algorithm


Abstract:

Distributed query processing 2010has become essential in today’s scenario to address the changing business needs of users. It aims to arrive at an optimal query processing plan for a given distributed query. This is a complex process as the number of possible query processing plans grows rapidly with increase in the number of sites used, and relations accessed, by the query. Therefore, there is a need to determine optimal query processing plans among all possible plans. The approach presented in this paper attempts to generate such optimal query processing plans using genetic algorithm. As per the approach, the query plans having the required data residing close to each other are considered more efficient and, therefore, are generated. These generated query plans would result in efficient query processing. Further, experimental results show that the approach is able to generate such optimal query processing plans in a fewer number of generations. Read More

Publication: International Conference on Data Storage and Data Engineering 2010

Publisher: IEEE Xplore

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

Keywords: Distributed Query Processing, Genetic Algorithm

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

Affiliations:

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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