Data Mining in Adaptive Control of Distributed Computing System Performance
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © - Issue 2011 by IJCTT Journal | ||
| Volume-2 Issue-2 | ||
| Year of Publication : 2011 | ||
| Authors :Ravi Kumar Gullapalli, Dr.Chelliah Muthusamy, Dr.A.Vinaya Babu. |
Ravi Kumar Gullapalli, Dr.Chelliah Muthusamy, Dr.A.Vinaya Babu. "Data Mining in Adaptive Control of Distributed Computing System Performance"International Journal of Computer Trends and Technology (IJCTT),V2(2):610-615 Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: -— The Distributed Computing Systems are significant building blocks in design and implementation of the business critical applications. It is always important for such environments to provide high performance for all kinds of workload variations. There are different solutions identified to deal with the performance problems in Distributed environments. There are recent investigations in exploring the feedback control based solutions in various computing environments. The self-managing capabilities are inherent qualities of Adaptive Control and such mechanisms are investigated to address performance problems in computing including distributed computing systems. The objective of Adaptive Controllers is to provide the intelligence in tuning the control parameters that would maintain the system in a desired state. In this paper we explore and identify the applicability of Data Mining based approaches to build Adaptive Controllers in self-managing the performance. We implemented a simple Adaptive Control using Time-Series Analysis. It predicts the frequency of occurrence of statements in a database so that the database driver can cache them according to the predicted values which demonstrates the feasibility of building Data Mining based Adaptive Controller.
References-
[1] S. Abdelwahed, N. Kandasamy and S. Neema, "A Control-Based Framework for Self-Managing Distributed Computing Systems",Workshop on Self-Managed Systems (WOSS`04), Newport Beach,CA USA, 2004.
[2] Joseph L Hellerstien, Kaan Katircioglu, and Maheswaran Surendra, “A Business-Oriented Optimization of Performance and Availability for Utility-Based Computing”, Journal on Selected Areas of Communications, Oct., 2005.
[3] Chris Toft et al, www.hpl.hp.com/techreports/2004/HPL-2004-49.pdf Self Managed Systems - A Control Theory Perspective HPL, 2004
[4] Joseph L. Hellerstein, Yixin Diao, Sujay Parekh, and Dawn Tilbury Feedback Control of Computing Systems, John Wiley 2004
[5] Ravi Kumar Gullapalli, Dr.Chelliah Muthusamy, Dr.A.Vinaya Babu, “Control Theory Applications in Java based Web and Enterprise Environments – A Survey”, IJACSA, Vol 2, No 8, 2011
[6] Wei Xu, Zhangxi Tan, Armando Fox, David Patterson, “Regulating Workload in J2EE Application Servers”, http://www.controlofsystems.org/febid2006/files/16225_Wei.pdf
Keywords— Data Mining, Adaptive Control, Distributed Computing Systems.