Cognitive Immunity Support for Large-Scale Autonomic Software Systems

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?