THE VISION OF AUTONOMIC COMPUTING

WHAT IS AUTONOMIC COMPUTING ? “ Autonomic Computing refers to computing infrastructure that adapts (automatically) to meet the demands of the applications that are in it “ A classical example for an Autonomic System – the human body These are intelligent systems that are able to operate, manage and improve their own operations with minimum or with no human intervention.

NEED FOR AUTONOMIC SYSTEMS Drivers increasing technological complexity increased size of computing infrastructure ballooning maintenance costs of infrastructure shortage of skilled labour

BENEFITS OF AUTONOMIC COMPUTING Self-Management

BENEFITS OF AUTONOMIC COMPUTING SELF-MANAGEMENT Self-healing detect improper operations and initiate corrective actions before they occur, without disrupting system applications or business processes Self-configuring adapt dynamically to changes in the IT environment with little human intervention

Self-protection detect and identify hostile behaviors and take autonomous actions to protect itself against intrusive behaviors Self-optimization efficiently maximize resource allocation and utilization so as to ensure optimal quality of service while continuing to meet users’ needs with minimal human intervention BENEFITS OF AUTONOMIC COMPUTING

CHARACTERISTICS OF AUTONOMIC COMPUTING To be Autonomic, a computing system needs to “ know itself ” – and comprise components that 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 Status quo – it always looks for ways to optimize it’s working

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 it’s parts to malfunction A Virtual World is no less than the Physical world, so an Autonomic Computing system must be an expert in self- protection An Autonomic Computing System knows it’s environment and the context surrounding it’s activity, and acting accordingly CHARACTERISTICS OF AUTONOMIC COMPUTING

An Autonomic Computing System cannot exist in a Hermetic Environment An Autonomic Computing System will anticipate the optimized resources needed while keeping it’s complexity hidden

AUTONOMIC ELEMENT ARCHITECTURE Monitor Analyze Execute Plan Knowledge Managed Element Autonomic Systems will be interactive collections of autonomic elements – individual system constituents that contain resources and deliver services to humans and other autonomic elements Autonomic Element Autonomic Manager

ENGINEERING CHALLENGES i. Life cycle of an Autonomic Element Design, test and verification Installation and configuration Monitoring and problem determination Upgrading Managing the life cycle

ENGINEERING CHALLENGES ii. Relationships among autonomic elements Specification Location Negotiation Provision Operation Termination

ENGINEERING CHALLENGES iii. System wide issues Security Privacy Trust etc iv. Goal specification

SCIENTIFIC CHALLENGES i. Behavioral abstractions and models ii. Robustness theory iii. Learning and optimization theory iv. Negotiation theory v. Automated statistical modeling

PATH TO AUTONOMIC COMPUTING Basic Level – IT professionals set up & monitor each infrastructure element. Managed Level – system management technologies used to collect information from disparate systems on fewer consoles. Predictive Level – Elements recognize patterns, predict optimal configuration & provide advice on course of action. Adaptive Level – Systems themselves can take the right actions based upon the info that is available to them. Autonomic Level – IT infrastructure governed by business policies & objectives. Users interact with the autonomic technology to monitor the business processes, alter the objectives, or both.

PROJECTS RELATED TO AUTONOMIC COMPUTING Organization Project IBM eLiza HP Virus throttling software Intel Itanium2 SUN N1 UCBR O C

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