AUTONOMIC COMPUTING

1. AUTONOMIC COMPUTING Jigar.B.Katariya (08291A0531) E.Mahesh (08291A0542)

2. Autonomic Computing Paradigm • To design and build computing systems capable of running themselves, adjusting to varying circumstances, and preparing their resources to handle most efficiently the workloads we put upon them. • Autonomic Computing is a concept that brings together many fields of computing with the purpose of creating computing systems that are reflective and self-adaptive. • Autonomic computing is generally considered to be a term first used by IBM in 2001 to describe computing systems that are said to be self configuring, self healing, self optimizing and self protecting.

3. Elements of Autonomic Computing

4. Comparison between existing computing and autonomic computing

5. Autonomic Computing Architecture

6. Control Flow The control loop: • collects information • analyzes data • finds a solution if needed • executes actions accordingly

7. Autonomic Manager

8. Self Managing in IT business

9. Challenges of Autonomic Computing Autonomic System challenges – Self-configuration in large-scale application. – Problem localization and automated remediation. – Decision making of coordination of optimizing process. – Self-protecting against active threats specific types of threats.

10. Conclusion • Solution of today’s increasing complexity in computing science Self-Management and dynamic adaptive behaviors • Still challenges in diverse fields of science and technology – Autonomic behavior in one field of science System managements, software engineering, etc. – Needs for a abstraction and co-operation in relevant fields.

11. Thank You Any Queries ? ?