Introduction to Autonomic Computing
                     Autonomic 
Computing
Introduction
Autonomic Computing is a type of visionary computing that has been 
started by IBM. This is made to make adaptive decisions that use high-
level policies. It has a feature of constant up-gradation using 
optimization and adaptation. 
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History
It was proposed by Jiming Liu in the year 2001. It uses artificial systems 
to solve complex problems using imitations like that of humans. On 
October 15 of the year 2001, IBM Research President, Paul Horn 
addressed an annual meeting. 
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History Cont.
He presented a solution to growing complexities and mentioned that the 
answer lied in building computer systems that could regulate 
themselves in a manner in which our nervous systems regulate and 
protect our bodies. E.g. Ant-colony optimization
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Need Of Autonomic 
Computing
With the increase in the demand for computers, computer-related 
problems are also increasing. They are becoming more and more 
complex. The complexity has become so much that there is a spike in 
demand for skilled workers.
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Areas Of Autonomic 
Computing
• Self-Configuration: The system must be able to configure itself 
automatically according to the changes in its environment.
• Self-Healing: IBM mentions that an autonomic system must have 
property by which it must be able to repair itself from errors and also 
route the functions away from trouble whenever they are 
encountered. 
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Areas Of Autonomic 
Computing Cont.
• Self-Optimization: According to IBM an autonomic system must be 
able to perform in an optimized manner and ensure that it follows an 
efficient algorithm for all computing operations. 
• Self-Protection: the IBM States that an autonomic system must be able 
to perform detection, identification, and protection from the security 
and system attacks so that systems’ security and integrity remain 
intact.
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Characteristics
• The Autonomic system knows itself. This means that it knows its 
components, specifications capacity, and the real-time status. It also 
has knowledge about its own, borrowed, and shared resources.
• It can configure itself again and again and run its setup automatically 
as and when required.
• It has the capability of optimizing itself by fine-tuning workflows.
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Characteristics Cont.
• It can heal itself. This is a way of mentioning that it can recover from 
failures.
• It can protect itself by detecting and identifying various attacks on it.
• It can open itself. This means that it must not be a proprietary solution 
and must implement open standards.
• It can hide. This means that it has the ability to allow resource 
optimization, by hiding its complexity.
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Autonomic Computing (AC) 
Architecture 
• The autonomic computing is needed so that it overcomes the problem 
of the increased complexity of the computing systems that acts to 
prevent further growth of the systems. There are several predictions 
with suggesting growth of 38% devices per annum with increased 
complexity.
• There is a need for autonomic computing in distributed computing 
because of the management of the computer networks complexes and 
a limiting factor in the future development of distributes computing 
systems. 
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Advantages
• It is an open-source.
• It is an evolutionary technology that adapts itself to new changes.
• It is optimized hence gives better efficiency and performance thereby 
taking lesser time in execution.
• It is very secure and can counter system and security attacks 
automatically.
• It has backup mechanisms that allow recovery from system failures 
and crashes.
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Disadvantages
• There will always be a possibility of the system crashing or 
malfunctioning.
• This would result in an increase in unemployment due to the lesser 
needs of people after it is implemented.
• The affordability would be an issue because it would be expensive.
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