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Autonomic Computing: A Fuzzy Control Approach towards Application Development

Autonomic Computing: A Fuzzy Control Approach towards Application Development

Harish S. Venkatarama, Kandasamy Chandra Sekaran
Copyright: © 2012 |Pages: 17
ISBN13: 9781609608453|ISBN10: 1609608453|EISBN13: 9781609608460
DOI: 10.4018/978-1-60960-845-3.ch005
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MLA

Venkatarama, Harish S., and Kandasamy Chandra Sekaran. "Autonomic Computing: A Fuzzy Control Approach towards Application Development." Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification, edited by Phan Cong-Vinh, IGI Global, 2012, pp. 118-134. https://doi.org/10.4018/978-1-60960-845-3.ch005

APA

Venkatarama, H. S. & Sekaran, K. C. (2012). Autonomic Computing: A Fuzzy Control Approach towards Application Development. In P. Cong-Vinh (Ed.), Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification (pp. 118-134). IGI Global. https://doi.org/10.4018/978-1-60960-845-3.ch005

Chicago

Venkatarama, Harish S., and Kandasamy Chandra Sekaran. "Autonomic Computing: A Fuzzy Control Approach towards Application Development." In Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification, edited by Phan Cong-Vinh, 118-134. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-60960-845-3.ch005

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Abstract

Autonomic computing (Salehie & Tahvildari, 2005) is a new paradigm to design, develop, deploy, and manage systems by taking inspiration from strategies used by biological systems. An autonomic system has four major characteristics: self-configure, self-heal, self-optimize, and self-protect. The autonomic computing architecture provides a blueprint for developing feedback control loops for self-managing systems. This observation suggests that control theory might provide guidance as to the structure of and requirements for autonomic managers. E-commerce is an area where an Autonomic Computing system could be very effectively deployed. E-commerce has created demand for high quality information technology services, and businesses seek ways to improve the quality of service in a cost-effective way. Properly adjusting tuning parameters for best values is time-consuming and skills-intensive. This chapter describes simulation environments to implement approaches to automate the tuning of MaxClients parameter of Apache web server using fuzzy controllers. These are illustrations of the self-optimizing characteristic of an autonomic computing system.

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