Autonomic Computing (Basics) Presentation

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This is the presentation I made for my seminar on the topic Autonomic Computing, which describes the Computing systems that can adjust themselves and adapt to various changes, autonomic-ally.

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Autonomic Computing (Basics) Presentation

  1. 1. Autonomic Computing Presented by:Jaspreet Singh (07511502710)
  2. 2. Why Autonomic Systems ? Technological advances High Growth More Complex Systems Brittle, Unmanageable, Insecure System and Application Complexity Growth
  3. 3. Concept Derived from Biology v Strategies based on biological systems v Inspired by Autonomic Nervous System in the human body. Defined as : - A self managing autonomous and ubiquitous computing environment that completely hides its complexity, thus providing the user with an interface that exactly meets his/her needs.
  4. 4. Four aspects of self-management often cited by IBM
  5. 5. Self Healing
  6. 6. Self Configuring Current Computing Corporate Data centers have multiple vendors and platforms. Installing, configuring and integrating systems is time consuming and error prone. Autonomic Computing Automated confihuration of components and systems follows high level policies. Rest of system adjusts automatically and seamlessly.
  7. 7. Self Protecting Anticipate, detect, identify and protect against attacks from anywhere. - Defining and managing user access to all computing rsources. - Protecting against unauthorized resource access, e.g. SSL - Detecting intrusions and repoting as they occur.
  8. 8. Self Optimizing Monitor and tune resources automatically - support operating in unpredictable environment. - Efficient maximization of resource utilization without human interference. Dynamic resource allocation and management. - Resource: Storage, databases, networks.
  9. 9. How it Works ? Autonomic Elements: Structure Fundamental atom of the architecture Managed element(s) Database, storage system, server, software app, etc. Plus one autonomic manager Responsible for: Providing its service Managing its own behavior in accordance with policies Interacting with other autonomic elements Autonomic Manager Analyze Monitor Plan Knowledge S E Managed Element Execute
  10. 10. Autonomic Elements: Interactions Relationships Dynamic, ephemeral, opportunistic Defined by rules and constraints Formed by agreement May be negotiated Full spectrum Peer-to-peer Hierarchical Subject to policies
  11. 11. Autonomic Systems: Composition of Autonomic Elements Workload Manager Arbiter Planner Provisioner Broker Server Network Sentinel Workload Manager Network Event Correlator Monitor Server Database Server Sentinel Database Monitor Broker Negotiator Aggregator Registry Registry Reputation Authority Storage Storage Storage Monitor
  12. 12. Conclusion • Solution of today’s increasing complexity in computing science Self-Management and dynamic adaptive behaviors • Still challenges in diverse fields of science and technology – Autonomic behavior in one field of science System managements, software engineering, etc. – Needs for a abstraction and co-operation in relevant fields. Autonomic computing is Solution of today’s increasing complexity in computing science
  13. 13. Thank You

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