1. Research Challenges of Autonomic Computing
Author: Jeffrey O. Kephart
Presented by: Djuradj Babich

2. Research Challenges of Autonomic Computing
Introduction
Characteristics of IT environments:
Complex
Heterogeneous (hardware, middleware, software)
Difficult to integrate, install, configure, tune, and maintain
Within few years, will become impossible to administer
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Research Challenges of Autonomic Computing

3. Research Challenges of Autonomic Computing
Complexity Solution
Systems comprised of self-managing components.
Self: Configuring, Healing, Optimizing, Protecting
Managing done in accordance with high-level objectives specified by humans.
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Research Challenges of Autonomic Computing

4. The Purpose of The Paper
Introduce IBM’s Autonomic Computing Initiative (ACI).
Decompose the grand challenge of autonomic computing into several of its constituent scientific and engineering challenges.
Provide pointers to initial efforts to address these challenges.
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Research Challenges of Autonomic Computing

5. Research Challenges of Autonomic Computing
Objectives
Describe a research framework
Present a subset of challenges:
Autonomic Element Challenges
Autonomic System Challenges
Human-Computer Challenges
Conclusion
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Research Challenges of Autonomic Computing

6. Research Challenges of Autonomic Computing
Research Framework
Helpful in defining, describing, and growing IBM’s current autonomic computing research program
Research space divided into 3 parts:
Autonomic Elements
Autonomic Systems
Human-Computer Interactions
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Research Challenges of Autonomic Computing

7. Research Challenges of Autonomic Computing
Autonomic Elements
Basic building blocks of autonomic systems
Their mutual interactions produce self-managing behavior of autonomic systems.
Three sub-branches distinguished within:
Specific Autonomic Elements
Generic Autonomic Element Technologies
Generic Autonomic Element Architectures, Tools, and Prototypes.
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Research Challenges of Autonomic Computing

8. Research Challenges of Autonomic Computing
Autonomic Systems
Composed of autonomic elements
Three sub-branches distinguished within:
Autonomic System Technologies
Autonomic System Architectures and Prototypes
Autonomic System Science
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Research Challenges of Autonomic Computing

9. Research Challenges of Autonomic Computing
Human Interaction
Managing done in accordance with high-level objectives specified by humans.
Two sub-branches distinguished within:
Human Studies
Policy
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Research Challenges of Autonomic Computing

10. Research Challenges of Autonomic Computing
Objectives
Describe a research framework
Present a subset of challenges:
Autonomic Element Challenges
Autonomic System Challenges
Human-Computer Challenges
Conclusion
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Research Challenges of Autonomic Computing

11. Autonomic Element Challenges
Specific Autonomic Elements
Improving the self-managing capability of specific components
Generic Autonomic Element Technologies
Applicable technologies (monitoring, forecasting, event correlation, rule execution, optimization, planning)
Generic Autonomic Element Architectures, Tools, and Prototypes.
Internal structure, helpful tools, and implementations
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Research Challenges of Autonomic Computing

12. Specific Autonomic Elements
More self-managing components
Emphasis: servers, DBMS, storage systems
Challenges numerous, but well-understood
New challenge introduced by IBM’s ACI:
Achieve effective interoperation by the autonomic elements
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Research Challenges of Autonomic Computing

13. Element Interoperation
Elements situated in autonomic systems
Cooperative intercommunication and interaction between elements essential
Requirements:
Standard interface (system architecture)
Ability to generate and supply needed info to other components
Ability to request and use info from other components
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Research Challenges of Autonomic Computing

14. Autonomic Element Challenges
Specific Autonomic Elements
Improving the self-managing capability of specific components
Generic Autonomic Element Technologies
Applicable technologies (monitoring, forecasting, event correlation, rule execution, optimization, planning)
Generic Autonomic Element Architectures, Tools, and Prototypes.
Internal structure, helpful tools, and implementations
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Research Challenges of Autonomic Computing

15. Monitoring and Analysis
Common methods for collecting and representing monitored data and log files.
Challenge: standardization
Solution effort: Common Base Event (OASIS Web Services Distributed Management Technical Committee)
Rule and correlation engines for analyzing monitored data and log files.
Challenge: set of rules and/or correlation expressions for condition description
Complication: correlation across multiple components
Solution effort: modeling, machine learning
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Research Challenges of Autonomic Computing

16. Research Challenges of Autonomic Computing
Event Correlation
Correlation extraction between low-level system measurements and high-level Service Level Objectives is based on modeling:
Map potential actions into probable outcomes
Forecast future demand and plan accordingly
Access models of other system components
Challenges:
Learn and readjust the models continually on the fly.
Adjust quickly to observations with a minimum of data and training time.
Adapt to conditions that are noisy and prone to fluctuations.
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Research Challenges of Autonomic Computing

17. Research Challenges of Autonomic Computing
Rule Execution
Rule authoring should be based on some form of machine learning, based on system-level goals coupled with historical observation
Challenges:
Random exploration
Several hundred tunable parameters
Learning process convergence
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Research Challenges of Autonomic Computing

18. Research Challenges of Autonomic Computing
Optimization
Optimization challenges overlap a good deal with those of learning.
Challenge:
Nonstationarity
Landscape changes due to effects such as:
Changing workload
Adaptive behavior by other autonomic elements
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Research Challenges of Autonomic Computing

19. Research Challenges of Autonomic Computing
Planning
Autonomic elements must conduct their planning in open environments that are not completely understood.
Challenge:
Need for planning techniques that handle incomplete domain specification
Need for continual assessment of plan completion progress
Need for generating and manipulating plan metadata
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Research Challenges of Autonomic Computing

20. Autonomic Element Challenges
Specific Autonomic Elements
Improving the self-managing capability of specific components
Generic Autonomic Element Technologies
Applicable technologies (monitoring, forecasting, event correlation, rule execution, optimization, planning)
Generic Autonomic Element Architectures, Tools, and Prototypes.
Internal structure, helpful tools, and implementations
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Research Challenges of Autonomic Computing

21. Autonomic Element Architecture
Support the need to manage and coordinate multiple threads of execution within the element.
Example: single task of honoring the terms of a service agreement with another element might entail:
Monitoring the variables of interest
Analyzing the extent to which they are being kept within agreed-upon bounds
Invoking a planner to determine a sequence of actions to improve performance
Use monitored data to improve internal model
Revise forecast of future workload
Revise model upon which the forecast is based
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Research Challenges of Autonomic Computing

22. Autonomic Element Architecture (cont.)
Challenge:
Develop an architecture (and functionality) for detecting and resolving conflicts that are bound to occur when an autonomic element cannot meet all of its obligations.
Example: Autonomic Database Element (Optimizer/Planner conflict)
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Research Challenges of Autonomic Computing

23. Autonomic Element Tools and Prototypes
Tools provide a set of autonomic element technologies, means for interconnecting them in accordance to architecture, and interfaces that permit appropriate interaction between elements.
Building and refining prototypes is essential for developing architectures and tools for autonomic elements.
Effort to offer some of the services: IBM’s Autonomic Computing toolkit
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Research Challenges of Autonomic Computing

24. Research Challenges of Autonomic Computing
Objectives
Describe a research framework
Present a subset of challenges:
Autonomic Element Challenges
Autonomic System Challenges
Human-Computer Challenges
Conclusion
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Research Challenges of Autonomic Computing

25. Autonomic System Challenges
Autonomic System Technologies
Generic technologies that entail interactions among multiple autonomic elements to achieve system level goals (problem determination and remediation, automated provisioning, installation, and configuration).
Autonomic System Architectures and Prototypes
System-level architectures that effectively govern interactions among autonomic elements.
Autonomic System Science
Fundamental science of large-scale autonomic computing systems (learning, stability, control, emergent behavior).
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Research Challenges of Autonomic Computing

26. Research Challenges of Autonomic Computing
Technologies
Self-Configuration
Self-Healing
Self-Optimization
Self-Protection
All four entail interactions among multiple autonomic elements
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Research Challenges of Autonomic Computing

27. System Self-Configuration
Challenges:
A new autonomic element integration
Automated deployment of large-scale application
Solution Effort:
Bootstrapping (registry interaction)
Integration of capacity planning, use of human expert knowledge, and schedulling technologies that generate workflows describing installation and configuration choreography
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Research Challenges of Autonomic Computing

28. Research Challenges of Autonomic Computing
System Self-Healing
Monitoring and aggregation of component metrics
Low-level events processed into higher-level assessments of the health
Rule and correlation technologies
Problem localization
Probe signals (overlapping)
Information theoretic techniques
Problem remediation
Database (symptom – action)
Recursive micro-rebooting
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Research Challenges of Autonomic Computing

29. System Self-Optimization
Workload management
Automated provisioning
Both based on objectives specified by humans
Performance models
Machine learning
Challenge: coordination
Incompatible goals and procedures
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Research Challenges of Autonomic Computing

30. System Self-Protection
Monitor system for compliance to security policies
Protect actively against threats as they occur
Challenge:
Intercommunication
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Research Challenges of Autonomic Computing

31. Autonomic System Challenges
Autonomic System Technologies
Generic technologies that entail interactions among multiple autonomic elements to achieve system level goals (problem determination and remediation, automated provisioning, installation, and configuration).
Autonomic System Architectures and Prototypes
System-level architectures that effectively govern interactions among autonomic elements.
Autonomic System Science
Fundamental science of large-scale autonomic computing systems (learning, stability, control, emergent behavior).
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Research Challenges of Autonomic Computing

32. Research Challenges of Autonomic Computing
System Architecture
Autonomic Elements must share
Common behaviors
Common interfaces
Common interaction patterns
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Research Challenges of Autonomic Computing

33. Autonomic System Challenges
Autonomic System Technologies
Generic technologies that entail interactions among multiple autonomic elements to achieve system level goals (problem determination and remediation, automated provisioning, installation, and configuration).
Autonomic System Architectures and Prototypes
System-level architectures that effectively govern interactions among autonomic elements.
Autonomic System Science
Fundamental science of large-scale autonomic computing systems (learning, stability, control, emergent behavior).
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Research Challenges of Autonomic Computing

34. Research Challenges of Autonomic Computing
System Science
Control and exploitation of emergent behavior
Economic mechanisms
Auctions and bilateral negotiations
Benchmarking
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Research Challenges of Autonomic Computing

35. Research Challenges of Autonomic Computing
Objectives
Describe a research framework
Present a subset of challenges:
Autonomic Element Challenges
Autonomic System Challenges
Human-Computer Challenges
Conclusion
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Research Challenges of Autonomic Computing

36. Interfacing with Humans
Develop new languages and metaphors
Specify objectives and goals in natural manner
Sufficiently expressive/structured
Intuitive interfaces
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Research Challenges of Autonomic Computing

37. Research Challenges of Autonomic Computing
Policies
Forms of expressing objectives
Low-level action-based
High-level, based on:
goals
Utility functions
Lingua franca
Difficult to specify
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Research Challenges of Autonomic Computing

38. Research Challenges of Autonomic Computing
Conclusion
Autonomic computing presents a challenge
Requires advances in several fields of science and technology
An open-platform autonomic computing prototype needed to support research
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Research Challenges of Autonomic Computing