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DC Field | Value | Language |
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dc.contributor.author | Venkatarama H.S. | |
dc.contributor.author | Chandra Sekaran K. | |
dc.date.accessioned | 2020-03-31T14:15:21Z | - |
dc.date.available | 2020-03-31T14:15:21Z | - |
dc.date.issued | 2011 | |
dc.identifier.citation | Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification, 2011, Vol., pp.118-134 | en_US |
dc.identifier.uri | 10.4018/978-1-60960-845-3.ch005 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/13760 | - |
dc.description.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. © 2012, IGI Global. | en_US |
dc.title | Autonomic computing: A fuzzy control approach towards application development | en_US |
dc.type | Book Chapter | en_US |
Appears in Collections: | 3. Book Chapters |
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