autonomic computing

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a detailed ppt on autoonmic computing

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Page 1: Autonomic Computing

WELCOME

Page 2: Autonomic Computing

AUTONOMIC COMPUTING

PRESENTED BY: NIKHIL P

S7 IT ROLL NO: 33

Page 3: Autonomic Computing

Motivation

Introduction

Why Autonomic Computing

Characteristics

Architecture

Application

Challenges

Conclusion

OVERVIEW

Page 4: Autonomic Computing

Present day IT environments are complex, heterogeneous in terms of software & hardware from multiple vendors.

Computing systems have evolved into millions of interconnected devices whose interactions create complex web on increasingly complex architecture.

MOTIVATION

Page 5: Autonomic Computing

Present day IT environment

Page 6: Autonomic Computing

Complexity of Information Technology

Page 7: Autonomic Computing

It is a term coined by IBM .

Principle similar to autonomic nervous system.

Its main aim is to make computer system more self managing and elastic, removing obstacles to growth and flexiblity.

Helps to address complexity by using technology to manage technology

INTRODUCTION

Page 8: Autonomic Computing

“Civilization advances by extending the number of important operations which we can perform without thinking about them”- ALFRED NORTH WHITEHEAD

This quote made by the preeminent mathematician Alfred Whitehead holds both the lock and the key to the next era of computing.

The high-tech industry has spent decades creating computer systems with ever- mounting degrees of complexity to solve a wide variety of business problems.

WHY AUTONOMIC COMPUTING

Page 9: Autonomic Computing

Ironically, complexity itself has become part of the problem. It’s a problem that's not going away, but will grow exponentially, just as our dependence on technology has

To overcome this problem IBM suggested a solution: build computer systems that regulate themselves much in the same way as our autonomous nervous systems regulates and protects our bodies.

This new model of computing is called autonomic computing

CONTD…..

Page 10: Autonomic Computing

“Intelligent” systems that:Manage complexityKnow themselvesContinuously tune themselvesAdapt to unpredictable conditionsPrevent and recover from failuresProvide a safe environment

The vision for Autonomic Computing

Page 11: Autonomic Computing

CHARACTERISTICS

Page 12: Autonomic Computing

Self-managing systems that deliver

Increased ResponsivenessAdapt to dynamically changing environments

OperationalEfficiencyTune resources and balance workloads to maximize use of IT resources

Business ResiliencyDiscover, diagnose,and act to prevent

disruptions

Secure Information and Resources

Anticipate, detect, identify, and protect

against attacks

Page 13: Autonomic Computing

SELF-CONFIGURATION

Adapt automatically to thedynamically changingenvironment Internal adaptation

– Add/remove new components– configures itself on the fly

External adaptation-Systems configure themselvesinto a global infrastructure

Page 14: Autonomic Computing

SELF-HEALING

Discover, diagnose and react to

disruptions without disruptingthe service environment Fault components should be

– detected– Isolated– Fixed– reintegrated

Page 15: Autonomic Computing

SELF-OPTIMIZATION

Monitor and tune resources

automatically– Support operating inunpredictable

environment– Efficiently maximization

ofresource utilization

withouthuman intervention

Dynamic resource allocationand workload management.

– Resource: Storage, databases,networks

– For example, Dynamic server clustering

Page 16: Autonomic Computing

SELF-PROTECTION

Anticipate, detect, identify

and protect againstattacks from anywhere

– Defining and managing user

access to all computingresources– Protecting againstunauthorized resourceaccess, e.g. SSL– Detecting intrusions andReporting as they occur

Page 17: Autonomic Computing

Self-aware System is aware of its internal state.

Context-aware System is aware of its execution environment.

Open System is able to operate in an heterogeneous environment.

Anticipatory System is able to anticipate the optimized resources needed.

And also

Page 18: Autonomic Computing

LEVELS OF AUTONOMIC MATURITY

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BASIC :

IT professionals manage everything by hand.

MANAGED :

Data are collected from the system (via sensors) and selected . The time is reduced.

PREDICTIVE :

Recognition of patterns and suggestion of a solution, the decision is made still by human.

CONTD…

Page 20: Autonomic Computing

ADAPTIVE :

The system makes and applies the solutions.

IT staff provides policies used for plans and monitors system’s actions.

AUTONOMIC :

Integrated IT components are collectively and dynamically managed by business rules and policies.

CONTD…

Page 21: Autonomic Computing

ARCHITECTURE

Autonomic element is the fundamental atom of the architecture

It consist of two parts Managed Element Autonomic Manager

Consist of one or more managed elements coupled with a single autonomic manager

Page 22: Autonomic Computing

A Managed Element can be:

Hardware resource, CPU, database, Application service, etc.

The components and functions of a single autonomic manager often referred to as the "MAPE loop" for Monitor, Analyze, Plan, and Execute, supplemented by a Knowledge base.

CONTD..

Page 23: Autonomic Computing

Core building blocks for an open architecture

Management using MAPE:– Monitoring managed elements and their external environment– Analyzing the gathered information– Planning and executing based on information

Page 24: Autonomic Computing

MONITOR

An autonomic manager monitors instrumentation data from multiple sensors in a system.

The sensors "sense" various aspects of the state of the monitored computing system.

This can include aspects of the hardware instrumentation, ambient information ,and aspects of the software components

CONTD…

Page 25: Autonomic Computing

ANALYZE

This component of the autonomic manager contains the intelligence required to interpret and correlate the above mentioned instrumentation data.

This component usually has the ability to consult historical data and to compare them with current state to detect significant changes.

CONTD…

Page 26: Autonomic Computing

PLAN Once an analysis report of the situation is completed, the

planning component can define a series of control actions that should bring the system to a normal operating range.

EXECUTE This component receives the series of action steps from the

planning component, and puts the plan into action.

It activates appropriate control points, or effectors, on the managed platform following the proper sequence and timing

CONTD…

Page 27: Autonomic Computing

KNOWLEDGE BASE

This serves as a repository of knowledge, such as historical data and policies, which can be utilized by the other components in their operation.

CONTD…

Page 28: Autonomic Computing

E−Sourcing

Problem determination

Complex analysis

Autonomic management

APPLICATIONS

Page 29: 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

−Needs for a abstraction and co-operation in relevant fields

CHALLENGES

Page 30: Autonomic Computing

Autonomic computing is:

Solution of today’s increasing complexity in computing science.

Self-Management and dynamic adaptive behaviors

“The new economics requires that systems be

autonomic: autoinstalling, automanaging,

autohealing, and autoprogramming.”

CONCLUSION

Page 31: Autonomic Computing

http:// www.ibm.com

http:// www.research.ibm.com

http:// www.wikipedia.org

REFERENCES

Page 32: Autonomic Computing

THANK U…

QUERIES…???