American Journal of Information Systems

ISSN (Print): 2374-1953

ISSN (Online): 2374-1988

Website: http://www.sciepub.com/journal/AJIS

Current Issue» Volume 2, Number 3 (2014)

Article

Estimating Plans along with Cost in Multiple Query Processing Environments by Applying Particle Swarm Optimization Technique

1Deaprtment of Computer Sc.&Engg., Ajay Binay Institute of Technology, Cuttack

2S.O.A. University, Bhubaneswar

3Government College of Engineering, Bhawanipatna


American Journal of Information Systems. 2014, 2(3), 52-55
DOI: 10.12691/ajis-2-3-2
Copyright © 2014 Science and Education Publishing

Cite this paper:
Sambit Kumar Mishra, Srikanta Pattnaik, Dulu patnaik. Estimating Plans along with Cost in Multiple Query Processing Environments by Applying Particle Swarm Optimization Technique. American Journal of Information Systems. 2014; 2(3):52-55. doi: 10.12691/ajis-2-3-2.

Correspondence to: Sambit  Kumar Mishra, Deaprtment of Computer Sc.&Engg., Ajay Binay Institute of Technology, Cuttack. Email: sambit_pr@rediffmail.com

Abstract

The Main idea of multiple query processing is to optimize a set of queries together and execute the common operations once. Major tasks in multiple query processing are common operation or expression identification and global execution plan construction. Query plans are generally derived from registered continuous queries. They are composed of operators, which perform the actual data processing, queries which buffer data as it moves between operators to hold state of operators. The complex part is to decompose queries and query plans and rearrange the sub queries and query plans on the network. The main functions to achieve an optimal query distribution are usually minimizing network usage and minimizing response time of queries. While dealing with query distribution problem, the challenges like modeling topology of the network, decomposing queries into some sub queries and sub query placement may be occurred. Operators are the basic data processing units in a query plan. An operator takes one or more streams as input and produces a stream as output. As in the traditional database management system, a plan for query connects a set of operators in a tree. The output of a child operator forms an input of its parent operator. In this paper it is aimed to retrieve the cost of query plans as well as cost of particles of swarm in multiple query processing environments by applying particle swarm optimization techniques.

Keywords

References

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Article

Computer System Users are like Fish

1Drexel University, Philadelphia, PA


American Journal of Information Systems. 2014, 2(3), 49-51
DOI: 10.12691/ajis-2-3-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Ralph M. DeFrangesco. Computer System Users are like Fish. American Journal of Information Systems. 2014; 2(3):49-51. doi: 10.12691/ajis-2-3-1.

Correspondence to: Ralph  M. DeFrangesco, Drexel University, Philadelphia, PA. Email: rd337@drexel.edu

Abstract

This paper has looked at the habits of computer users when faced with a slow system and has drawn a direct correlation between how they react and fish population dynamics. A survey has been presented that supports the proposed theory.

Keywords

References

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