1 / 17

Cognitive Immunity Support for Large-Scale Autonomic Software Systems

Cognitive Immunity Support for Large-Scale Autonomic Software Systems. David Lamb D.Lamb@2005.ljmu.ac.uk Room 608, ext. 2280 http://www.staff.ljmu.ac.uk/cmpdlamb Supervisors: Dr. Dhiya Al-Jumeily, Prof. A Taleb-Bendiab School of CMS, Liverpool John Moores University. Overview.

breindel
Download Presentation

Cognitive Immunity Support for Large-Scale Autonomic Software Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Cognitive Immunity Support for Large-Scale Autonomic Software Systems David Lamb D.Lamb@2005.ljmu.ac.uk Room 608, ext. 2280 http://www.staff.ljmu.ac.uk/cmpdlamb Supervisors: Dr. Dhiya Al-Jumeily, Prof. A Taleb-Bendiab School of CMS, Liverpool John Moores University

  2. Overview • Background – Situating the problem • Research Literature Review • Motivation – Why this line of research • Current Research – overview • Research Objectives • Identified Problem Areas • Future Work – plans for the future Annual Research Conference - 2006

  3. Background • Setting the scene • Who else is doing similar work? • Overview of literature review: • Cognitive Immunity • Artificial Immune Systems • Cognitive Systems • Machine Learning, etc • Complex Networks / Graph Theory Annual Research Conference - 2006

  4. Background: Cognitive Immunity • Influential/Related work: • Notion of CI discussed as one approach in DARPA Self-Regenerative Systems research programme • DARPA define CI systems as those: • Capable of “accurately diagnosing root causes of system problems ” • Capable of “taking effective corrective action [appropriate to problem diagnoses]” Annual Research Conference - 2006

  5. Background: AIS Artificial Immune Systems • Many aspects influenced by Biologically-Inspired Computing • Bottom-up approach • Creates complex behaviour from simple interactions • Therefore, may scale well to manage complex computer systems • Some examples: • Biological Immune System • Artificial Immune Systems • Self/Non-self discrimination & Pattern Recognition • Danger Theory • Evolution: GAs • Emergence: Ants, Swarms, etc Annual Research Conference - 2006

  6. Background: Cognitive Systems • ALCS (Anticipatory Learning Classifier Systems) • ALP – Anticipatory Learning Process • Observes environment • Generates specialised rules that describes the observed behaviour: • Of the form (Condition  Action  Effect) • GGM – Genetic Generalisation Mechanism • Uses genetic selection mechanism to generalise • Keeps rule set correct and compact Annual Research Conference - 2006

  7. Background: Machine Learning • Machine Learning • Novelty Detection • Statistics – clustering of types • Neural Networks – trained networks as classifiers • SOMs – self-organising classifiers • Chance Discovery • Change-based KB, Dialogue approach, Key graphs • Reinforcement Learning Annual Research Conference - 2006

  8. Background: Graph Theory • Graph Theory • May provide a method to understand complex systems’ organisation • Identifies nodes and connections • Understanding which nodes form “hubs” • Complex Networks • E.g. Small world and scale-free networks • Scale Free robust in random failures Annual Research Conference - 2006

  9. Motivation • What makes this research worthwhile? • Brief overview of: • Static vs. Dynamic software design • Benefits of Dynamic/Evolving systems • Problems involved in dynamic system design Annual Research Conference - 2006

  10. Motivation: Software Design • Traditional Static System Design Methods • Well understood • Limitations • Resistant to change • Inadequate for modelling complex systems • Design Methods for Complex, Large-Scale, Dynamic Systems • Would overcome some limitations • New Problems and Challenges Annual Research Conference - 2006

  11. Motivation: Dynamic Systems • Dynamic System Design • Should allow the system to: • Evolve at runtime • Allows optimal (re) configuration and organisation • Respond to changing environments • Resist threats • However, brings its own problems: • How to design it? • How to best implement it? • How to support it? Annual Research Conference - 2006

  12. Current Research • What have I done? • Literature Review • Prepared Research Proposal • What has that achieved? • Identified Research Objectives • Further Research Problems Annual Research Conference - 2006

  13. Current Research: Literature Review • Literature Review • Machine Learning Techniques • Artificial Immune Systems • Cognitive Immunity • Cognitive Systems • Complex Networks / Graph Theory Annual Research Conference - 2006

  14. Current Research: Objectives • Literature review led to research proposal, identifying the following objectives: • Further Literature Review of Cognitive Systems • Creation of a programming model and framework for Evolving, Self-Healing systems that demonstrate Cognitive Immunity: • Understand Requirements of this approach • How to develop and support this approach • How to apply this approach Annual Research Conference - 2006

  15. Current Research: Problems • Identified Research Problems relevant to creating a system capable of Cognitive Immunity: • Lack of formalised programming models • Adaptation to Environment • Environmental Sensing • Plan Generation • Plan Enactment • Benevolent System Observation • Tuning, Improvement, Optimisation Annual Research Conference - 2006

  16. Future Work • Further Literature Review • More on ALCS, including a prototype implementation • Research other Cognitive-type systems • Graph Theory, and approaches to Complex Networks • Other suitable models for self-organising systems • Definition of Requirements Model • …leading to the creation of the related programming model • Further development and generalisation of the model Annual Research Conference - 2006

  17. Thank you for listening! Any Questions?

More Related