1 / 31

Outline

Complexity Concerns in Autonomic and Self-Organising Systems Prof. A. Taleb-Bendiab School of Computing Liverpool John Moores University email: a.talebbendiab@livjm.ac.uk http://www.cms.livjm.ac.uk/taleb. Outline. Drivers for a paradigm shift Autonomic Grid Computing Autonomic Computing

keena
Download Presentation

Outline

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. Complexity Concerns in Autonomic and Self-Organising SystemsProf. A. Taleb-BendiabSchool of ComputingLiverpool John Moores Universityemail: a.talebbendiab@livjm.ac.ukhttp://www.cms.livjm.ac.uk/taleb Prof. A. Taleb-Bendiab, talk: UWA’06, Guest Speaker, Date: 31/08/2014, Slide: 1

  2. Outline • Drivers for a paradigm shift • Autonomic Grid Computing • Autonomic Computing • Setting the Scene for • Drivers for a paradigm shift • Quest for a new theoretical framework • Recent bio-inspired initiatives • SAS, DASADA, SRS and ANTS • Understanding autonomic software engineering • Definitions and state of the art • Challenges and open research questions • Complexity Networks • Self-organising systems • Complex random networks • Conclusions • Q&A Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 2

  3. Emerging Networked Landscapes Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 3

  4. Drivers for a Paradigm Shift #2 • Modern Expectations • High-Availability -- 24x7 delivery • near-100% availability is becoming mandatory for e-commerce, enterprise apps, online services, ISPs • Change • Support rapid deployment of new hw/sw, services, etc • Maintainability • Provide flexible systems admin. env. • reduce system administrators tasks, complexity and cost • Just-in-time scalability • Allow flexible system up scaling without sacrificing performance, availability or maintainability • evolutionary growth and adaptation • Survivability • Full malleability Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 4

  5. A Shift Towards  What? • Key question is not only how to achieve the above listed modern expectations as: • a single metric/attribute or a cost-effective combination of them all • But IBM argues that it’s how to reduce the cost and complexity of achieving that • Bio-inspired models – Autonomic Computing • Management by delegation • Etc. • So where to next? Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 5

  6. Definitions #2 • Can be defined as: • 3. Yet Another • can operate independently of (or with limited) human intervention, thus hiding their systems’ design and management complexity including intricacies of the automation of laborious administration tasks, recovery from unanticipated system’s failure, and/or self-protection from security vulnerability. Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 6

  7. Characterising AC Capabilities • Characterising AC Systems • A software system is autonomic, if it possesses the following capabilities: • Self-configuring— choosing a suitable behaviour, based on user preferences, context, … • Self-tuning— choosing behaviours that optimize certain qualities (performance, year-end profits, …) • Self-repairing— shifting execution to another behaviour, given that the current one is failing • Self-protecting— choosing a behaviour that minimizes risks (attacks, viruses, …) Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 7

  8. Autonomic Computing Inspired by the “autonomic” function of the human central nervous system. software systems that take care of the mundane elements of systems management themselves, allowing human operatives to concentrate on more important work. Major Recent Initiatives • 4 major research thrusts: • Biologically-inspired diversity: genetically diverse computing fabric • “Cognitive immunity” and self-healing: see automated cyber immune response and system regeneration. • Granular, scalable redundancy: This research thrust area will increase the practicality of redundancy techniques. • Reasoning about the insider threat to preempt insider attacks and detect system overrun. • A 2020 vision of a class of space exploration missions termed nanoswarms, where many cooperating picospacecraft or intelligent spacecraft work in teams to explore the asteroid belt, based on the efficiency and coordination of hive culture. • Some Recent Initiatives • SAS -- Self-Adaptive Systems (DARPA, 1997) • DASADA -- Dynamic Assembly for Systems’ Adaptability, Dependability, and Assurance (DARPA, 2000) • AC -- Autonomic Computing (IBM, 2001) • ACom- Autonomic Communication (EU, 2003) • SRS -- Self-Regenerative Systems (DARPA, 2003) • ANTS -- Autonomous Nano-Technology Swarm (NASA) • KP -- Knowledge Plane (MIT, DARPA, 2004) • Defined by Laddaga in the 1997 DARPA Broad Agency Announcement as: • “...software that evaluates its own performance and changes behaviour when the evaluation indicates that it is not accomplishing what the software is intended to do...”. • To adapt, the system reacts to environmental change - the problem is recognising the need for change, then planning, enacting and verifying the change - these are self-managing concerns Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 8

  9. Remaining Research Challenges • Host-Based • Complexity Paradox • Autonomic computing aims to reduce admin. costs, hide system complexity and intricacy, • Though, their designs are becoming more complex • as yet are poorly understood as echoed by D. Garlan 2005 • “… how do we design, build, and evolve such sw systems so that they can meet given—and evolving—requirements ...” • Incremental deployment of AC capabilities in legacy systems. • AOP-based evolution, Interoperation • Support functional and non-functional requirements for autonomy. • Evaluation mechanisms and metrics [ref] • Governance vs Autonomy Paradox • Balancing and adjusting governance and autonomy • Programming, control and Interaction Models • Complex-Based • Self-organisation • Complex and random Networks Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 9

  10. Progress to Date #1 • Has been informed by a set of design paradigms • Model-based vs Self-Organising Systems design models • Top-down vs bottom-up • Applying and/or revisiting: • cybernetic principles • control systems theory, regulation, reward and sanctions • Decision theory, Complexity theory • DAI and CI • dynamic planning, deliberative models, ML • Middleware support • self-awareness, reflection and deliberation • Autonomic Software Architecture, etc. Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 10

  11. The Story so Far #1 • Currently design models of the 1st generation ”autonomic systems” employ; • Explicit managed autonomy via policies and rule sets predefining at design-time all extraneous behaviour using constructs such as; • Event Condition Action, Design by contract • Separation of concerns – AOP, etc. • State-of-the-art of autonomic systems designs including; • autonomic software models and architecture, standards • tools and techniques to support • the design, modelling, analysis • and evolution of autonomic software • Define associated models for their • programming, control • interaction models with human and/or other non-AC systems (legacy). • Delegation of authority and its adjustment Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 11

  12. Story so far #2 • More recent work is focusing on scalable methods for specifying dynamic behaviour of autonomic systems. • Axiomatic vs algebraic modelling • FOL based calculi Vs process algebra • Evolving • policies and control model • Structural/organisational model • Bounded autonomy and adjustments • Unifying models for • model-based and SOS approaches for autonomic systems engineering and management Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 12

  13. Our Approaches #1 • More recent theoretical work is focusing on scalable methods for specifying and enacting dynamic behaviour of autonomic systems • Autonomic Systems Engineering • Related Work: IBMblueprint (www-03.ibm.com/autonomic/pdfs/ACBP2_2004-10-04.pdf) • An autonomic manager contains a continuous control loop that monitors activities and takes actions to adjust the system to meet business objectives • Autonomic managers learn from past experience to build action plans • Elements need to be instrumented consistently, based on open standards • Our model • Model-based Approach • Systems theory, design patterns, design grammar and service-oriented programming • A. Taleb-Bendiab, D.W. Bustard, R. Sterritt, A. Laws, M. Randles, F. Keenan, P. Miseldine, "Model-Based Self-Managing Systems Engineering", in Proceedings of the 16th International Workshop on Database and Expert Systems Applications (DEXA’05),  SAACS'05: 3rd International Workshop on Self-Adaptable and Autonomic Computing Systems, pp., • David Bustard, Roy Sterritt, A. Taleb-Bendiab, A. Laws, M. Randles, F. Keenan, 05, "Towards a Systemic Approach to Autonomic Systems Engineering", EASE'2005. • David Bustard, Roy Sterritt, A. Taleb-Bendiab, A. Laws, M. 06, "Autonomic System Design Based on the Integrated Use of SSM and VSM", to appear in AI Review, Vol. , No. , Springer, ISSN 0269-2821. • K. Liu, A. Taleb-Bendiab, 05, "Presenting a Case for a Principled Approach to Citizen, Business and Technology Integration in e-Government Services: Challenges and Research Opportunities", Egov'05. Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 13

  14. Our Approaches #2 • Emergence-based Approach • Complexity: Complex Systems • Seth Bullock and D. Cliff (HP Report, Ref.) • Complexity and Emerging Behaviour in IT Systems Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 14

  15. Achievements So far … Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 15

  16. P2P Self-Organising Overlays: Grids Show Example -1 Request monitor (via MSDL) Readings Deploy Sensor (via SADL) Sensor Provider Show Example-4 Sensor & Actuator Framework Show Example-2 Readings as XML Inject Show Example-5 Show Example-3 Edit Sensors Select Sensors Consumer Sensors Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 16

  17. Modelling Autonomy #1 • Algebraic specification • Process Algebra • CSP • Static model checking and dynamic software analysis • Key States and Transitions are not enough • Intelligent organisation emerges as in natural systems • Mathematical Modelling of Collectives • Formal Model – Situation Calculus – Knowledge • Consequential Emergence • Novel Emergence Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 17

  18. Modelling Autonomy #2 • Our model • Using SSC used to formalizes the behaviour of dynamically changing systems FOL (McCarthy, 1963).. • Support concurrent actions and timing constraints. • Each situation can be viewed as a history of previous actions. • Action, guards and time can be modelled at deliberation points in an autonomic setting. • M. Randles, A. Taleb-Bendiab, Philip Miseldine, Andy Laws, "Adjustable Deliberation of Self-Managing Systems", ECBS 2005: 449-456. [ppt] Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 18

  19. Modelling Autonomy #3 • Evolving and Adjustable Autonomy • Via compositional model and evolution of • Software services (components) • Software governance (Control) via • Formal modelling of norms, policies • Enactment support – from spec. to code using Neptune language • M. Randles, A. Taleb-Bendiab, P. Miseldine, 05, "Mind out of Programmable Matter: Exploring Unified Models of Emergent System Autonomy for Collective Self-Regenerative Systems", Extended Abstract, the 2nd GSFC/IEEE Workshop on Radical Agent Concepts (WRAC'05), NASA GSFC Visitor's Center, Greenbelt, MD, 20th-22nd September 2005. • Miseldine, P., Taleb-Bendiab A. “A Programmatic Approach to Applying Sympathetic and Parasympathetic Autonomic Systems to Software Design”, Self-Organisation and Autonomic Informatics (ISBN I-58603-577-0), Hans Czap, Rainer Unland, Cherif Branki, Huaglory Tianfield (Eds.), pp:3-17, IOS Press, Amsterdam, 2005.Awarded "Most Innovative Paper" at Conference • Miseldine, P., Taleb-Bendiab, A., “CA-SPA: Balancing the Crosscutting Concerns of Governance Autonomy in Trusted Software”, IEEE International Workshop on Trusted and Autonomic Computing Systems within AINA 2006. Vienna, Austria. April 2006. Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 19

  20. Self-Governance Theory Deliberative layer using the EBDI model Formal modelling of norms, etiquette, rules of play deployed via CA-SPA constructs Enactment support – from spec. to code Governing Autonomy Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 20

  21. Programming Autonomic Systems • Neptune Meta-Language • Integrated Development Environment: • Miseldine, P., Taleb-Bendiab A. A Programmatic Approach to Applying Sympathetic and Parasympathetic Autonomic Systems to Software Design. to appear in the 2005 International Conference on Self-Organization and Adaptation of Multi-agent and Grid Systems (SOAS’2005). Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 21

  22. Example 1: A Grid-Based Decision Systems Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 22

  23. Organisation in Complexity • Engendering and Monitoring for Known Organising Behaviour • Scale-Free • Small World • Clustering • Observation and Control • Observer influenced system • Observer monitored system Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 23

  24. What Next? • Engendering and Monitoring for Known Organising Behaviour • Scale-Free • Small World • Clustering • Observation and Control • Observer influenced system • Observer monitored system • Bounded Autonomy Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 24

  25. Case Study- NASA ANTS Project • Leader Spacecraft form a Team • Imperatives Define Team Goals • Imperative I • To Keep Worker Spacecraft Connected • Imperative II • Number of Leader Spacecraft must be Maintained over a Certain Number • Logical Consequences Emerge Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 25

  26. Detection and Influencing • Preferential Attachment • Node degree di is number of connection on node i • Typical Measure • (i, j) means node i is connected to node j • C is set of connections • Large number indicates very connected hub structure Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 26

  27. Some Experiments … Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 27

  28. Results Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 28

  29. Learning Control Rules as an Emerging Behaviour Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 29

  30. Acknowledgements • Acknowledgements • My thanks to the Team •  • Useful Links • www.cms.livjm.ac.uk/2nrich • www.cms.livjm.ac.uk/cloud • www.cms.livjm.ac.uk/taleb Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 30

  31. That’s the end – so I’m off ! Prof. A. Taleb-Bendiab, talk: UWA’06 Guest Speaker, Date: 31/08/2014, Slide: 31

More Related