Conclusion (Conclude Introduction to Autonomic Computing)

By reading this paper you can gain the knowledge about Autonomic Computing. I detailed it under the following sub topics.

 1.0 Introduction
 2.0 Why need Autonomic?
 3.0 Major Researches 
           3.1 Research projects in Autonomic computing.
           3.2 University research projects in autonomic computing
4.0 Four basic elements of autonomic computing
           4.4 self-protecting
           AutonomicComputing Vs Current Computing
5.0 Autonomic computing architecture
6.0. Autonomic computing today
           6.1. Initiatives of autonomic computing 
           6.2. Benefits
           6.3. Applications
7.0 What happen if does not have autonomic in the future?
8.0 Autonomic Computing Research Issues and Challenges
9.0 Future direction of Autonomic computing
10.0 Conclusion

10.0 Conclusion

In this paper, we introduced the autonomic computing paradigm, which is inspired by biological systems such as the autonomic human nervous system, and enables the development of self-managing computing systems and applications. The systems use autonomic strategies and algorithms to handle complexity and uncertainties with minimum human intervention.

Several research efforts focused on enabling the autonomic properties address four main areas: self-healing, self-protection, self-configuration, and self-optimization. Projects in both industry and academia, have addressed autonomic behaviors at all levels, from the hardware level to software systems and applications. At the hardware level, systems may be dynamically upgradable, while at the operating system level, active operating system code may be replaced dynamically. Efforts have also focused on autonomic middle-ware, programming systems and run-time. At the application level, self optimizing databases and web servers dynamically reconfigure to adapt service performance.

However, achieving overall autonomic behaviors remains an open and significant challenge, which will be accomplished through a combination of process changes, skills evolution, new technologies and architecture, and open industry standards.


Thanks to researchers who are researches about autonomic computing.


[1] Autonomic Computing: An Overview_ Manish Parashar and Salim Hariri
[2]Autonomous Computing Systems by Neil Joseph Steiner
[7]P. Horn, Autonomic Computing: IBM’s Perspective on the State of Information Technology, IBM Corporation (October 15, 2001); available at http://www.research.ibm.com/autonomic/manifesto/autonomic_computing.pdf.
[9]Research Challenges in Autonomic Computing by Jeff Kephart IBM Research
High Performance Distributed Computing Laboratory, University of Arizona
The Applied Software Systems Laboratory, Rutgers, The State University of New Jersey
[11]Evaluation issues in Autonomic Computing, Julie A. McCann, Markus Huebscher
Department Of Computing, Imperial College London
[12]The Vision of Autonomic Computing, Jeffrey O. Kephart, David M. Chess,IBM Thomas J.Watson Research Center
[13]Learning Procedures for Autonomic Computing by Tessa Lau, Daniel Oblinger, Lawrence Bergman, and Vittorio Castelli
[14]The dawning of the autonomic computing era
by A. G. Ganek ,T. A. Corbi
[18] http://www.research.ibm.com/

By K.H.L.R. Perera

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