- Autonomic computing is a discipline that aims to create self-managing computer systems inspired by biological systems like the human central nervous system.
- It aims to overcome the complexity and inability to effectively maintain current and emerging computer systems by making systems self-configuring, self-healing, self-optimizing and self-protecting.
- Early research projects are exploring techniques like recovery-oriented computing, self-securing storage, and swarm-based autonomous systems to achieve attributes of self-management in systems.
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 homes
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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
Exchanges
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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 21st
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5. IBM's 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
Manifesto
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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 Projects
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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 level
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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 networks
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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
involvement
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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 malfunction
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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
hidden
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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 PC's, 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 due
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to self-healing. 13
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.
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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.
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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. 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 in
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the near future. 17
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 Technology
05/05/2010 Journal, vol. 8, 2004, p. 279–290. 18
19. Bibliography (Cont.)
• A. Garcia, T. Batista, A. Rashid, and C. Sant'Anna,
"Autonomic computing: emerging trends and open
problems," SIGSOFT Softw Eng Notes, vol. 30, 2005,
pp. 1-7.
• P. Horn, "Autonomic Computing: IBM's 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 autonomic
05/05/2010 computing," Computer, 2003, pp. 41-50. 19