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Optimized Access Strategies for a Distributed Database Design
Rajinder Singh, Gurvinder Singh
Pages - 102 - 110     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 2   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
Distributed Database, Query Optimization, Genetic Algorithms
Abstract Distributed Database Query Optimization has been an active area of research for Database research Community in this decade. Research work mostly involves mathematical programming and evolving new algorithm design techniques in order to minimize the combined cost of storing the database, processing transactions and communication amongst various sites of storage. The complete problem and most of its subsets as well are NP-Hard. Most of proposed solutions till date are based on use of Enumerative Techniques or using Heuristics. In this paper we have shown benefits of using innovative Genetic Algorithms (GA) for optimizing the sequence of sub-query operations over the enumerative methods and heuristics. A stochastic simulator has been designed and experimental results show encouraging improvements in decreasing the total cost of a query. An exhaustive enumerative method is also applied and solutions are compared with that of GA on various parameters of a Distributed Query, like up to 12 joins and 10 sites. Keywords: Distributed Query Optimization, Database Statistics, Query Execution Plan, Genetic Algorithms, Operation Allocation.
CITED BY (1)  
1 Tâmbulea, l., darabant, a. s., & varga, v. (2014). data transfer optimization in distributed database query processing. studia universitatis babes-bolyai, informatica, 59(1).
1 Google Scholar 
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1 Ozsu & Valduriez. “Principles of Distributed Database Systems” Pearson Education 2nd Edition,pp. 228-298.
2 March,Rho,”Characterisation and Analysis of a Nested Genetic Algorithm for Distributed Database Design”.,Seoul Journal of Business pp 85-121 vol2,Number 1. 1995.
3 Goldberg David.E “Genetic Algorithms in search, Optimization & Learning” Pearson Education 2nd Edition,pp. 1-55.
4 Sacco,G. & Yao”Query Optimisation in Distributed Database Systems”1982,Advances in Computers,21,225-53.
5 Yu,C.T,Chang” Distributed Query Processing “ ACM Computing Surveys,16,399-433.
6 Graefe,G”Query Evalution Texhniques for a large Database” ACM Computing Surveys,25,73-90, .1993.
7 March,S.T.,Rho “Allocating Data and Operations to nodes in a distributed database design”. IEEE Trans. On knowledge and Data Engg.,7(2). 1995.
8 Kossman,D. “The state of the art in Distributed Query Processing”.,ACM Computing Surveys.,32(4),422-469. 2000.
9 Cheng,C.H.Lee,W-K,Wong,K-F, “A Genetic Agorithm based clustering approach for database partitioning “ IEEE Transactions on System,Man,Cybernetics,32(3),215-230. 2002.
10 Zehai Zhou,”Using Heuristics and Genetic Algorithms for Large Scale Database Query Optimization,” Journal of Information and Computing Sciences,Acadeamim Press- 2007.
11 Apers,P.M.G,1988”Data Allocation in Distributed Database Systems”,ACM Trans. On Database Syatems,.13(3),263-304
12 Tamhankar,A.M & Ram”Database Fragmentation & Allocation: An Integrated Methodolgy and case study.” IEEE Transactions on System,Man,Cybernetics,28(3),288-305.
13 Martin,T,Lam& Russel”An Evaluation of Site Selection Algorithms for Distributed Query Processing”’The Compuer Journal,33(1),61-70,1990.
14 Frieder, O. Baru”Site and Quey Sechduling policies in Microcomputer Database Systems” IEEE Trans. On knowledge and Data Engg.,6(4).1994.
15 Johansson,JM,March,ST,Naumann”Modelling Network Latency Paralell Processing In Distributed Database design”,Decision Sciences,34(4) 677-706 2003.
Associate Professor Rajinder Singh
- India
Associate Professor Gurvinder Singh
- India