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AUTONOMOUS AND AUYTONOMIC SYSTEM FOR SELF MANAGING AND SELF DIRECTING SERVICE ABSTRACT Proceedings of the third IEEE International Engineering of Autonomic and Autonomous Systems (Ease 2006), IEEE Computer Society (Los Ala mitos, CA, USA), ISBN 0-7695-2544-X, Pages 1-16 DOI: 10.11.09/EASE .2006.18 Autonomous and Autonomic Systems (AAS) Autonomous : Auto = self nomous=law One who gives oneself his own law. Autonomic: Auto= self nomic=management One who manages automatically. The Task Force on Autonomous and Autonomic Systems (TF AAS) was established to address research issues concerned with creating self-directing and self-managing systems (self ware or self working properties). The overarching vision of AAS is the creation of self-directing and self managing systems in accordance with high-level guidance from humans to address today's concerns of complexity and total cost of ownership while meeting tomorrow's needs for pervasive and ubiquitous computation and communication. The AAS overlaps to some degree with many others providing opportunities for collaboration to meet the grand challenges, but focuses on specifically addressing architectures, frameworks, paradigms, componen ts, tools, environments, languages , applications and lessons for Autonomous and Autonomic Computing and Communications (Systems). The complexity of modern middleware, and software solutions, is growing at an expon ential rate. Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators. While much has been publi shed on ³ar chitecture´ and ³ function´ for producing such systems, little has been written about the engineering of s elf- managing systems as a distinct paradigm. In this paper we suggest a straw-man for engineering of autonomic systems that is based on two essential tracks: a set of engineering principles that should guide the planning of autonomic systems and their interfaces and secondly a set of mathematical foundations upon which such systems can best be constructed. These foundational attributes are intended to guide the thinking of R&D organizations pursuing the development of autonomic computing capability. The role of architecture and standards is also discussed , highlighting their r ole in inter- componen t management. EXISTING SYSTEM

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AUTONOMOUS AND

AUYTONOMIC SYSTEM

FOR SELF MANAGING

AND SELF DIRECTING

SERVICE

ABSTRACT

Proceedings of the third IEEE

International Engineering of Autonomic

and Autonomous Systems (Ease 2006),

IEEE Computer Society (Los Alamitos,

CA, USA),

ISBN 0-7695-2544-X, Pages 1-16

DOI: 10.11.09/EASE.2006.18

Autonomous and Autonomic Systems(AAS)

Autonomous: Auto = self 

nomous=lawOne who gives oneself his

own law.

Autonomic: Auto= self 

nomic=management

One who manages

automatically.

The Task Force on Autonomous and

Autonomic Systems (TFAAS) was

established to address research issues

concerned with creating self-directing and

self-managing systems (self ware or self working properties).

The overarching vision of AAS is the

creation of self-directing and self managing systems in accordance with

high-level guidance from humans toaddress today's concerns of complexity

and total cost of ownership while meeting

tomorrow's needs for pervasive andubiquitous computation and

communication.

The AAS overlaps to some degree with

many others providing opportunities for 

collaboration to meet the grand challenges,but focuses on specifically addressing

architectures, frameworks, paradigms,

components, tools, environments,

languages, applications and lessons for 

Autonomous and Autonomic Computing

and Communications (Systems).

The complexity of modern middleware,

and software solutions, is growing at anexponential rate. Only self-managing, or 

autonomic computing technology canreasonably stem the confusion this

complexity brings to bear on humanadministrators. While much has been

published on ³architecture´ and ³function´for producing such systems, little has been

written about the engineering of self-

managing systems as a distinct paradigm.

In this paper we suggest a straw-man

for engineering of autonomic systems that

is based on two essential tracks: a set of 

engineering principles that should guide

the planning of autonomic systems and

their interfaces and secondly a set of 

mathematical foundations upon which

such systems can best be constructed.

These foundational attributes are intended

to guide the thinking of R&Dorganizations pursuing the development of 

autonomic computing capability. The roleof architecture and standards is also

discussed, highlighting their role in inter-

component management.

EXISTING SYSTEM

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Semi-automatic systems need theassistance from humans and cannot work 

fully by itself and cannot decide on itself.

Human are prone to make errors and hence

leads to major problems in complex

systems.

Humans cannot perform their work in

extreme conditions and impossible

environments like outer space.

Some situation may lead threat to human

life.

PROPOSED SYSTEM

Autonomous and autonomic systems adapt

themselves to dynamically changing

environments.

Autonomous and autonomic systems

detects, identifies and protects against

attacks and utilizes maximum resources.

It has a wide range of applicability fromthe basic home requirements to advanced

military and outer space robotic machines.

It works in extreme conditions and in outer space without any problem and performs

its work efficiently.

WORKING

PRINCIPLE

ORDER OF WORKING:

1  COLLECT: This is the first phase

called as the collect phase. It collects

the samples from the external

environment. This is the first step of analyzing dynamic environment.

2  ANALYSE: This is the second phase

called as analysis where the collected

samples will be analyzed and checked.

3  DECIDE: Based on the analysis of the

previous step a suitable decision will

be taken so that the system will not getany kind of harm from external

dynamic environment.

4  ACT: The autonomous system will acton the decision and behaves as decided

and responses to the environment.

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Autonomous Nanobot 

Autonomousnanobot acting as a neuron

which perform similar work of a human

nervous system in sending signals from thebody to different parts of body which is anautonomic system.

Nanorobotics is the technology of creatingmachines or robots at or close to the

microscopic scale of ananometer (10

í9meters). More

specifically, nanorobotics refers to the still

largely hypotheticalnanotechnology engineering discipline of 

designing and building nanorobots,devices ranging in size from 0.1-10

micrometers and constructed of nanoscaleor molecular components.

Nanotechnology promises futuristic

applications such as microscopic robots

that assemble other machines or travel

inside the body to deliver drugs or do

microsurgery.These machines will face

some unique physics. At small scales,

fluids appear as viscous as molasses, andBrownian motion makes everything

incessantly shake. Taking inspiration from

the biological motors of living cells,

chemists are learning how to utilize protein

dynamics to power micro size and

nanosize machines with catalytic reactions.

Autonomous Satellite System 

The development of autonomous satellite

servicing systems potentially has a wide

range of uses in both military and civil

space programs. Obvious applications in

the military markets include re-fueling of 

surveillance and reconnaissance satellitesas one means to increase both their 

lifetime and utilization factor. In the civil

space sector, a similar need exists to refuel

operational systems that are fuel limited

but whose data is essential (e.g.,

communications, navigation, weather satellites).

This autonomous satellite system uses the

same principles of working as just saidabove which has 4 phases which are

collect, analyze, decide, and act. Hence itperforms very well in the outer space

which is a dynamic environment.

These devices are crucial for research and

development organization since they will

be working continuously and sending

information about their collected results

back to earth via infrared communication

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desirable in fields such as spaceexploration, cleaning floors, mowing

lawns, and waste water treatment.

A fully autonomous robot has the ability to

1 Gain information about the environment.

2 Work for an extended period without

human intervention.

3 Move either all or part of itself 

throughout its operating environment

without human assistance.

4 Avoid situations that are harmful to

people, property, or itself unless those are

part of its design specifications.

ADVANTAGES 

Much of the work in autonomic systemsinvolves improving the automated

management of technology like self configuration,self healing,self security, and

self optimizing. Examples include:

� improving the self-description of components to allow automated

installation;

� improving network protocols to adapt to

changes in other layers of the network 

stack; and

� changing protocols at a fundamental

level to provide more adaptive responses

to changing network conditions

DISADVANTAGES

Total cost to implement and to deploy the

system is very high.

Any hardware or software failure leads to

permanent failure of the entire system.

It can be used only for complex system

and tasks since the cost of its productionare very high.

CONCLUSIONS

Autonomic computing is, in general, a

type of computing model in which thesystem exhibits self healing, self-

configuring, self-protecting, and self managing properties. It is designed to

mimic the human body's nervous system.ust as the autonomic nervous system acts

and reacts to stimuli independent of theindividual's conscious input, an autonomic

computing

Environment operates organically in

response to the input it collects; also error 

rate of an autonomous system is almost

nill and hence a higher performance can be

achieved.

Autonomous and Autonomic system is a

self-management system which is based on

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high level guidance from humans, isincreasingly

being accepted as a means forward indesigning

reliable systems that both hide complexity

from the

user and control IT management costs.

Autonomic computing is an emerging area

of study and

a ³Grand Challenge´ for the entire I/T

community to

Address in earnest.