Autonomic Computing: Vision or Reality - Presentation


Published on

Autonomic computing is a new computing paradigm which combines multiple disciplines of computer science with the sole aim of developing self-managing computer systems. Dating from early 2001, it is one of the most recent paradigm shifts, and as such it is still in a research-only phase, however, attracting a lot of business investors in the process.

The following survey presents in a clear and appropriately detailed manner the problem of computer science which autonomic computing tries to solve, the details of the proposed solution, together with the some of the immediate and long-term benefits it will provide. Moreover, the survey outlines the basic principles which define a system as an autonomic one, and presents a novel method of designing autonomic systems. Closing the survey are two sections which briefly outline the most prominent research projects on autonomic computing, together with a distiled summary of the major challenges which will be faced by businesses in the process of adopting autonomic systems.

Published in: Technology
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Autonomic Computing: Vision or Reality - Presentation

  1. 1. Autonomic Computing Ivo Neskovic
  2. 2. It all started in 1876... • Alexander Graham Bell • Inventor of the telephone • One of the most influential inventions ever • Widely adopted • By 1886 nearly 150.000 Americans had telephones in their homes05/05/2010 2
  3. 3. The Telephony Crisis of 1920 • Manual telephone switchboards • By the year of 1980, every woman in the U.S. would have to work as a switchboard operator • The Solution: Automatic Branch Exchanges05/05/2010 3
  4. 4. Flash Forward to 2001 • The telephone is the computer • The telephone network is the Internet • The telephone operators are system administrators • Predictions are that by the year 2010, 200 million workers will have to maintain trillion systems • We need to invent the automatic branch exchanges of the 21st05/05/2010 century 4
  5. 5. IBMs Vision • Paul Horn, Senior Vice President of Research • Creator of the term autonomic computing • Systems need to develop self- managing capabilities • System administrators will no longer be needed for maintaining computer systems • Author of the Autonomic Computing Manifesto05/05/2010 5
  6. 6. Outline • The Solution • What is Autonomic Computing? • Designing Autonomic Computer Systems • Eight Principles of Autonomic Computing • The Benefits • Short-term IT related benefits • Long-term, Higher Order Benefits • Research Projects05/05/2010 6
  7. 7. The Solution • End users of computer systems are the primary stakeholders • They desire: • Intuitive interaction with the system • Their involvement in the smooth running of the system to be minimal to none • Conclusion: the system has to be autonomic • The only know truly autonomic system is the human central nervous system • Sends control messages to the organs in the human body at a sub-concious level05/05/2010 7
  8. 8. Central Nervous System05/05/2010 8
  9. 9. What is Autonomic Computing? • A network of autonomic, smart computing components which provide the user with the desired functionality without a concious effort • A new computing paradigm, transferring the focus from computing to data • Key concept: Allow users to access data from multiple distributed points, with great transparency to how this is achieved • Focus in IT industry must change from increasing processing speed and storage capacity to developing large distributed, self-managing, self-diagnostic networks05/05/2010 9
  10. 10. Designing Autonomic Computer Systems • Change in design, implementation and support is imminent • Three basic principles: • Flexible. Data transfer through a platform/hardware independent approach • Accessible. The system must be always accessible; always on • Transparent. The system will function and adapt to the users needs without any human involvement05/05/2010 10
  11. 11. Eight Principles of Autonomic Computing • An autonomic computing system needs to ”know itself” - its components must also possess a system identity • An autonomic computing system must configure and reconfigure itself under varying and unpredictable conditions • An autonomic computing system never settles for the status quo - it always looks for ways to optimize its workings • An autonomic computing system must perform something akin to healing - it must be able to recover from routine and extraordinary events that might cause some of its parts to malfunction05/05/2010 11
  12. 12. Eight Principles of Autonomic Computing (Cont.) • An autonomic computing system must detect, identify and protect itself against various types of attacks to maintain overall system security and integrity • An autonomic computing system must know its environment and the context surrounding its activity, and act accordingly • An autonomic computing system cannot exist in a hermetic environment • An autonomic computing system will anticipate the optimized resources needed while keeping its complexity hidden05/05/2010 12
  13. 13. The Benefits • Short-Term IT Related Benefits • Simplified user experience through a more responsive, real-time system. • Cost-savings – scale to use. • Scaled power, storage and costs that optimize usage across both hardware and software. • Full use of idle processing power, including home PCs, through networked systems. • Natural language queries allow deeper and more accurate returns. • Seamless access to multiple file types. Open standards will allow users to pull data from all potential sources by re-formatting on the fly. • Stability. High availability. High security system. Fewer system or network errors due05/05/2010 to self-healing. 13
  14. 14. The Benefits (Cont.) • Long-Term, Higher Order Benefits • Realize the vision of enablement by shifting available resources to higher-order business. • Embedding autonomic capabilities in client or access devices, servers, storage systems, middle-ware and network itself. • Constructing autonomic federated systems. • Achieving end-to-end service level management. • Collaboration and global problem-solving. • Massive simulation – weather, medical – complex calculations like protein folding.05/05/2010 14
  15. 15. Research Projects • Berkeley University of California: Recovery-Oriented Computing • Joint Berkeley/Stanford project. • Investigating novel techniques for building highly-dependable Internet services. • Emphasizes recovery from failures rather than failure-avoidance. • Carnegie Mellon University: Self-Securing Storage & Devices • Enabling the storage device to safeguard data even when the client OS is compromised. • Server-embedded security that cannot be disabled by any software (event the OS). • Self-securing storage server actively looks for suspicious behaviour.05/05/2010 15
  16. 16. Research Projects (Cont.) • Georgia Institute of Technology: Qfabric • Closely integrating applications and resource managers in the Quality of Service management. • Achieved by tying applications and resource managers through the same event-based control path. • Application and resource managers can interact freely to ensure optimal resource scheduling and adaptations. • NASA: Autonomous Nanotechnology Swarm (ANTS) • 1,000 pico-class spacecraft. • Each spacecraft caries only one instrument. • Swarm will be self-protecting, self-healing,05/05/2010 self-configuring and self-optimizing. 16
  17. 17. Summary • Inspired by biology. • Evolved as a discipline to create software systems and applications that self- manage. • Main purpose is to overcome the complexities and inability to maintain current and emerging systems effectively. • IT industry, software engineering and development must change the current focus and the process for developing autonomic systems. • Still in the early research-only phases, with hindsight of real projects forming in05/05/2010 the near future. 17
  18. 18. Bibliography • S. Ahmed, S.I. Ahamed, M. Sharmin, and M.M. Haque, "Self-healing for autonomic pervasive computing," Proceedings of the 2007 ACM symposium on Applied computing - SAC 07, 2007, p. 110. • J. Cheng, W. Cheng, and R. Nagpal, "Robust and self- repairing formation control for swarms of mobile agents," Proceedings of the National Conference on Artificial Intelligence, Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999, 2005, p. 59. • S. Dobson, R. Sterritt, P. Nixon, and M. Hinchey, "Fulfilling the Vision of Autonomic Computing," IEEE Computer, vol. 43, 2010, p. 35–41. • E. Mainsah, "Autonomic computing: the next era of computing," Electronics and Communication Engineering, 2002, pp. 8-9. • B. Melcher and B. Mitchell, "Towards an autonomic framework: Self-configuring network services and developing autonomic applications," Intel Technology05/05/2010 Journal, vol. 8, 2004, p. 279–290. 18
  19. 19. Bibliography (Cont.) • A. Garcia, T. Batista, A. Rashid, and C. SantAnna, "Autonomic computing: emerging trends and open problems," SIGSOFT Softw Eng Notes, vol. 30, 2005, pp. 1-7. • P. Horn, "Autonomic Computing: IBMs Perspective on the State of Information Technology," Computing Systems, 2002. • M.C. Huebscher and J.A. McCann, "A survey of autonomic computing—degrees, models, and applications," ACM Computing Surveys (CSUR), vol. 40, 2008. • IBM, "White Paper: An architectural blueprint for autonomic computing," white paper, 2005. • J. Kephart, "Research challenges of autonomic computing," Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005., 2005, pp. 15-22. • J. Kephart and D. Chess, "The vision of autonomic05/05/2010 computing," Computer, 2003, pp. 41-50. 19