UbiCom Book Slides

1. UbiCom Book Slides Chapter 10 Autonomous Systems & Artificial Life (All Parts, Short Version) Stefan Poslad http://www.eecs.qmul.ac.uk/people/stefan/ubicom Ubiquitous computing: smart devices, environmentsand interaction

2. Chapter 10: Overview Chapter 10 focuses on: • Internal system properties: autonomous • External interaction with any type of environment • Focussing more on physical environment • A lesser extent focussing on Human & ICT environments Ubiquitous computing: smart devices, environments and interaction

3. Introduction Ubiquitous computing: smart devices, environments and interaction

4. Related Chapter Links • Sometimes autonomy is seen as a property of intelligence (Chapter 8) • Designing UbiCom systems to be autonomous enables them to be self-managed (chapter 12) Ubiquitous computing: smart devices, environments and interaction

5. Chapter 10: Overview The slides for this chapter are split into several parts: • Part A: Autonomous Systems: Basics  • Part B: Reflective & Self-Aware Systems • Part C: Self-Management & Autonomic Computing • Part D: Complex Systems • Part E: Artificial Life Ubiquitous computing: smart devices, environments and interaction

7. Part A Outline • Basics  • Types of Autonomous System • Autonomous Intelligent Systems • Limitation of Autonomous Systems • Self-* Properties of Intra-Action Ubiquitous computing: smart devices, environments and interaction

8. Introduction • Term autonomous originates from the Greek terms autos meaning self and nomos meaning rule or law. • Autonomy is considered to be a core property of UbiCom systems • enabling systems to operate independently • without external intervention. • Autonomous systems operate at the opposite end of the spectrum to completely manual, interactive, HCI systems. • Without autonomous systems, sheer number & variety of tasks in an advanced technological society that require human interaction would overwhelm us and make system operation unmanageable. Ubiquitous computing: smart devices, environments and interaction

9. Automatic System An automatic system is specific type of autonomous system designed to • Act without human intervention • Execute specific preset processes • Work in deterministic & dynamic environments • Incorporate simple models of environment behaviour • Incorporate algorithms to control the environment (closed-loop control systems). Ubiquitous computing: smart devices, environments and interaction

10. Autonomous Systems More general types of systems than automatic systems are needed. Why? Ubiquitous computing: smart devices, environments and interaction

11. Autonomous Systems: Design 4 major designs for general autonomous systems: • Dynamically reusable and extensible components • EDA and context-aware system • Hybrid goal-based (Section 8.3.4) and environment model based IS systems (section 8.3.3). • Autonomic Systems Ubiquitous computing: smart devices, environments and interaction

12. Autonomous Systems Design: Component-based • Autonomous systems can be designed to consist of dynamically reusable and extensible components There are different types of component autonomy / cohesion • Design autonomy • Interface Autonomy • Components use of SOA (Section 3.2.4). • Component functions could be reprogrammable e.g., using mobile code (Section 4.2.2). • These types of systems tend to have a strong notion of ICT environment autonomy • but not of their physical & human environment autonomy. Ubiquitous computing: smart devices, environments and interaction

13. Autonomous Systems Design: EDA, Context-Aware • Autonomous systems which operate in dynamic environments can be designed to ? • These systems tend to focus on: • Physical world awareness and user awareness • How the system decides how to adapt to such context changes & how they affect current, active, user goals (Section 7.2). Ubiquitous computing: smart devices, environments and interaction

14. Autonomous Systems Design: IS • Autonomous systems can be designed to be hybrid goal-based (Section 8.3.4) and environment model based IS systems (section 8.3.3). • Generally, focus of such systems is on supporting a notion of social autonomy or self-interested behaviour rather than on supporting ICT environment autonomy or physical environment autonomy. Ubiquitous computing: smart devices, environments and interaction

15. Autonomous Systems Design: Autonomic • Autonomous systems can be designed to be autonomic. How? • Key challenges? Ubiquitous computing: smart devices, environments and interaction

16. Autonomous Intelligent Systems • Autonomy is a key property of an IS • An IS may have a physical embodiment or software embodiment which may be free to be executed in any part of a internetworked virtual computer. Ubiquitous computing: smart devices, environments and interaction

17. Autonomous Types: Self Governance • There are two main kinds of autonomy: • self-governance • independence. Ubiquitous computing: smart devices, environments and interaction

18. Social / Organisational Autonomy • Often an IS will delegate actions to another one, making it dependent on actions of another IS • But  risk of failure for the delegated actions because of misunderstandings, disagreements and conflicts, error, unknown private utilities and self-interests may operate. • Designs for IS to cope with risk of delegation of actions? Ubiquitous computing: smart devices, environments and interaction

19. Autonomous versus Automatic • Automatic refers to a system being self-steering • To be self-steering requires a system to sense its environment & act upon it based upon what it has sensed • Autonomous are generally first automatic systems but which are extended so that they become self-governed. Ubiquitous computing: smart devices, environments and interaction

20. Limitation of Autonomous Systems • Systems designed to be autonomous over parts of its life-cycle • Challenges in supporting full autonomy? Ubiquitous computing: smart devices, environments and interaction

21. Self-* Properties of Intra-Action • Application processes are not influenced by external behaviour or control but are dependent on, or driven by, their internal behaviour • Attempts to externally pertubate the system will be resisted and moderated in autonomous systems. • Some system behaviour is decentralised and local, • However, other system behaviour is community-wide, global • Set of so called self-* properties is a way to characterise autonomous systems • These are also called the self-self-x or auto-* properties • Set of self-* properties that need to be supported depends upon the application domain and system design. Ubiquitous computing: smart devices, environments and interaction

22. Self-Star Properties • Need to model complex systems whose components have some autonomy and propensity to maintain and improve their own operation in the face of external environment perturbations, e.g., • Autonomic computing • Organic Computing • IS Ubiquitous computing: smart devices, environments and interaction

23. Self-Star Properties • Self-star model focuses on doing things self-contained or doing things internally • List of types of self-star system could be expanded • to incorporate self-referencing, self-interaction (intranets) etc. Ubiquitous computing: smart devices, environments and interaction

24. Self-star Properties: Examples • Self-Configuring • Self-Regulating • Self-Optimising, Self-Tuning • Self-Learning • Self-Healing, Self-Recovery • Self-Protecting • Self-Aware • Self-Inspection Self-Decision • Self-Interested • Self-Organising • Self-Creating, Self-Assembly, Self-Replicating • Self-Evolution, Emergence • Self-Managing or self-governing • Self-Describing Self-Explaining • Self-representing Ubiquitous computing: smart devices, environments and interaction

25. Part B Outline • Self-Awareness  • Self-Describing and Self-Explaining Systems • Self-Modifying Systems based upon Reflective Computation Ubiquitous computing: smart devices, environments and interaction

26. Context-Awareness versus Self-Awareness • Context-awareness is complementary to self-awareness. • Context-awareness (Section 7) focuses on an awareness of a system’s external environment (user, ICT, Physical ) context, periodically sensing this, automatically detecting significant change, and using this to adapt the internal system’s behaviour to external environment behaviour. • An associated design issue is what degree if any, an awareness the system needs of its own internal behaviour. • Self-awareness focuses on monitoring its internal behaviour in order to optimise its behaviour Ubiquitous computing: smart devices, environments and interaction

27. Self-Awareness • Basic design is that an ICT system does not process itself or is not aware of its own actions. Why not? • Is basic designs for Intelligent Systems inherently self-aware? • Useful that systems know its internal state & how it acts? Ubiquitous computing: smart devices, environments and interaction

28. Self-Awareness: Applications • Optimising internal resource use • Robots, e.g., robot arms • Self-explaining systems Ubiquitous computing: smart devices, environments and interaction

29. External Descriptions & Explanations • Common reasons why systems are less usable? • Intelligibility to user etc Disadvantages to using an external operator’s manual? • How to support self-descriptions? • Using internal (to the device) resources • Hybrid: device can be queried for the address, e.g., URL, of its description, but which resides elsewhere in its environment, e.g., the Cooltown and Semacode, Tagging (Chapter 6) Ubiquitous computing: smart devices, environments and interaction

30. Self-Describing & Self-Explaining Systems • A self-describing system is able to describe itself from the perspective of what • A self-explaining system describes itself from the perspective of how and why. • Self-descriptions & self-explanations can be supported at multi-levels • Systems can also provide mechanisms and interfaces to output their external for other meta-level processes or diagnostics • e.g., the JTAG interface (Section 6.6.1). • Devices know their state in relation to their plans and goals • etc Ubiquitous computing: smart devices, environments and interaction

31. Self-Description: Limitations & Design Issues • Limitations? • Design issues? • How rich are descriptions? • How structured are they? • How full versus short? • Internal versus external and on-line versus off-line, • Co-located versus external not co-located (Section 6.2). Ubiquitous computing: smart devices, environments and interaction

32. Reflection • Reflection is the process by which a system can observe its own structure and behaviour, reason about these and possibly modify these Reflection has several benefits for UbiCom? • Reflection is considered in more detail in Section 10.3.3. Ubiquitous computing: smart devices, environments and interaction

33. Reflective System Architecture To support reflection, reflective computation is done by a system at a meta-level about its own operation at the application or base level of the system

34. Reflection There are three elements to the reflection process: • Instrumentation • introspection • adaptation Ubiquitous computing: smart devices, environments and interaction

35. Reflection Design • Combined system reflection & operation representation • Separate system reflection & operation representation • Design issues? • How to support & enable this meta-level processing • How the reflection is represented, • what triggers the reflection • what parts of the system can be reflected upon • performance & security aspects of using reflection. Ubiquitous computing: smart devices, environments and interaction

36. Reflection Design • Reflection as an extension to middleware model? • Reflective model is often applied as a design for context-aware systems. How? Ubiquitous computing: smart devices, environments and interaction

37. Part C: Outline • Basics  • Self-* Management & Control • Autonomic Computing Design • Autonomic Computing Applications • Modelling and Management Self-Star Systems Ubiquitous computing: smart devices, environments and interaction

38. Autonomic Computing • Motivation for autonomic systems was to deal with the obstacle of IT system complexity: • “The growing complexity of the IT infrastructure threatens to undermine the very benefits information technology aims to provide” (Horn, 2001). • Autonomic computing is one of the most well-known types of self-* system • Autonomic computing is also referred to as self-managing systems or self-governing systems. • Autonomic computing was inspired through analogy with the human body’s nervous system. • Autonomic systems can be constructed as group of locally interacting autonomous entities that cooperate to maintain system wide behaviour without any external control. Ubiquitous computing: smart devices, environments and interaction

39. Types of Self-* Control Compared Global Global Policies Policies Policies Policies Control Loop Local Local Local Local Local Local Policies Local Policies Local Local Local Local Local

40. Key Autonomic Computing Properties Different definitions of key properties • Keplar: • self-configuration • self-optimisation • self-healing • self-protection. • Ganek • self-awareness • context-aware adaptation • planning to control behaviours constrained by system policies. Ubiquitous computing: smart devices, environments and interaction

41. Taxonomy for Basic Self-star Properties • General Classification for basic self-star properties of systems can be based upon? Ubiquitous computing: smart devices, environments and interaction

42. Taxonomy for Basic Self-star Properties • Hence, agent designs oriented to these environments can form the basis of designs of autonomic systems • Specific properties relate to the type of organisation: • Spatially dependent, • Role-based, • Group-based, • Resource access control • Self protecting. Ubiquitous computing: smart devices, environments and interaction

43. Taxonomy for Basic Self-star Properties • Methods for coordination of autonomous systems are dependent on the type of organisation • Tuning servers individually (also called locally or on a microscopic scale) may be beneficial • However in other applications, tuning servers individually, may not be optimal Ubiquitous computing: smart devices, environments and interaction

44. Autonomic Computing Design

45. Autonomic Computing: Architectural Models 5 basic components: • a user interface (task manager) • an autonomic manager with an autonomic control loop • a knowledge base about the managed resources including management policies • a standardised interface to access managed resources (TouchPoint) • service-based communications network, the ESB (Section 3.3.3.8). Ubiquitous computing: smart devices, environments and interaction

46. Designs to Support Self-* System Components • SNMP and the MIB can be used to implement TouchPoint & part of knowledgebase (Chapter 12) • Semantic and Syntactical metadata wrappers can be used to describe the structures of resources in richer ways. • Sensors can poll resources or receive notifications about events in resources (Chapters 3,6) • Designs for autonomic control loop can be based on: • feedback control algorithms (Section 6.6) • action selection loop design of intelligent systems (Section 8.3). Ubiquitous computing: smart devices, environments and interaction

47. Designs for Self-* System

48. Different Levels of Support for Self-* Properties Self-star systems can be designed to support different maturity levels of self-star properties: • Basic • Managed • Predictive • Adaptive • Autonomic Ubiquitous computing: smart devices, environments and interaction

49. Autonomic Computing Applications • Channels allocation to meet peak demand for calls in different mobile phone cells • Load-balancing in servers to meet a designated QoS under variable external processor loads • Intrusion detection: • Protecting Critical Infrastructures (SCADA): Ubiquitous computing: smart devices, environments and interaction

50. Modelling & Managing Self-* Systems • How to model and mange systems which are dynamic decentralised and to an extent, non-deterministic? • Unit testing and formal proofs? • Statistical methods? • Equation based computation methods ? • Equation free computation methods ? • Time series chaos theory analysis? Ubiquitous computing: smart devices, environments and interaction