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Large-scale adaptive systems

Large-scale adaptive systems. Lecture 1: Introduction & concepts. Dr. Stefan Dulman s.o.dulman@tudelft.nl. Acknowledgements. This course was built using material from: Adaptive Systems by prof . Giovanna di Martzo Serugendo http://www.dcs.bbk.ac.uk/~dimarzo/courses/as.html

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Large-scale adaptive systems

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  1. Large-scale adaptive systems Lecture 1: Introduction & concepts Dr. Stefan Dulman s.o.dulman@tudelft.nl

  2. Acknowledgements • This course was built using material from: • Adaptive Systems by prof. Giovanna diMartzoSerugendohttp://www.dcs.bbk.ac.uk/~dimarzo/courses/as.html • Complex Systems by prof. OzalpBabaogluhttp://www.cs.unibo.it/~babaoglu/courses/cas/ • Organic Computing by prof. Kay Römerhttp://www.iti.uni-luebeck.de/index.php?id=roemer&L=1 Large-scale adaptive systems - Stefan Dulman

  3. Why a course on adaptive systems? • Traditional engineered systems • Client/Server • Characteristics: • Centralized • Scalability? • Single point of failure? • Traffic load? Large-scale adaptive systems - Stefan Dulman

  4. Motivation • Current engineered systems • P2P systems • Grid systems • Agent-based systems • Ad-hoc networks • Characteristics: • Decentralized • Autonomous components • Heterogeneity • Pervasiveness • Hybrid control http://robobees.seas.harvard.edu/ Large-scale adaptive systems - Stefan Dulman

  5. Future engineered systems • Self-managing systems • Self-configuring, self-healing, self-protecting, self-optimising • Self-organising networking systems • Overlay networks • Intrusion Detection Systems • Sentient Computing • Smart spaces • Intelligent transport services • Characteristics • Large scale (number/worldwide) • Decentralised Control • Self-organisation • Adaptive Systems Large-scale adaptive systems - Stefan Dulman

  6. Science fiction? • Programmable matter • Claytronicsproject • www.cs.cmu.edu/~claytronics/ • Kitchen of the future • www.itechfuture.com Large-scale adaptive systems - Stefan Dulman

  7. Engineered Adaptive Systems • Inspiration • From natural systems • Social insects: ants / wasps / termites • Biological systems: immune system • Interactions mechanisms leading to: • Decentralised control • Self-organisation • Emergent Behaviour • Adaptation and Robustness • Artificial / ad-hoc techniques Large-scale adaptive systems - Stefan Dulman

  8. Aims and scope of the course • Study of (engineered) adaptive systems • Engineering techniques • Inspired from natural systems … OR … • Developed specifically for artificial systems • Engineering Issues • Verification • Control • Etc. Large-scale adaptive systems - Stefan Dulman

  9. Lecture 1 Organization Motivation for adaptive systems Basic concepts and examples Organization issues Large-scale adaptive systems - Stefan Dulman

  10. Concepts Self-Organisation Emergent Phenomena Decentralised Control Adaptation Dynamic Change Complexity Large-scale adaptive systems - Stefan Dulman

  11. Self-Organisation • Some definitions … “The capacity to spontaneously produce a new organization in case of environmental changes without external control.” • Local rules + local information = behavior “Self-organisation is a process in which pattern at the global level of a system emerges solely from numerous interactions among the lower-level components of the system. Moreover, the rules specifying interactions among the system’s components are executed using only local information, without reference to the global pattern.” • Camazine et al. Large-scale adaptive systems - Stefan Dulman

  12. Self-Organisation • Natural systems • Non-living systems • Physical Process of pattern formation • Living systems • Biological Process of pattern formation • Animals (stripes, coat patterns) • Plants • Collective behaviour • Micro-organisms (cells) • Social behaviour: Swarms • Human behaviour • Engineered systems Large-scale adaptive systems - Stefan Dulman http://www.inf.u-szeged.hu/saso10/presentations/BudapestHelbing.pdf

  13. Self Organization – Non living systems BénardConvection Cells Snowflakes http://www.its.caltech.edu/~atomic/snowcrystals/ Large-scale adaptive systems - Stefan Dulman

  14. Self Organization – Living systems At individual level At collective level Large-scale adaptive systems - Stefan Dulman

  15. Self-Organisation • Strong & weak “Strong self-organising systems are those systems where there is re-organisation with no explicit central control, either internal or external.” • Dimarzo et al. (2005) “Weak self-organising systems are those systems where, from an internal point of view, there is re-organisation under an internal central control or planning.” • Dimarzo et al. (2005) “Self-organisation is the process enabling a system to change its organisation in case of environmental changes without explicit external command.” Large-scale adaptive systems - Stefan Dulman

  16. Self-Organisation • Engineered Systems • Distributed problem-solving • Travelling salesman problem • Routing in networks • Graph partitioning • But also … • Overlay networks • Distributed operating systems • P2P systems Large-scale adaptive systems - Stefan Dulman

  17. Emergent Phenomena • Some definitions “The whole is more than the sum of the parts” - Holland (1998) “A structure (pattern, property or function), not explicitly represented at the level of the individual components (lower level), and which appears at the level of the system (higher level).” Large-scale adaptive systems - Stefan Dulman

  18. Emergent Phenomena • Structure-formation • Structure = pattern / function / property • Examples: • Sand dune ripples • Zebra stripes • Emergence of consciousness in human • Emerges from neurons interactions • Shortest path to food found by foraging ants • Engineered systems: • TSP: shortest path to visit all cities Large-scale adaptive systems - Stefan Dulman

  19. Emergent Phenomena • External Observer • Emergent phenomena have a meaning for an observer external to the system but not for the system itself. • Emergent Phenomena • Observed patterns or functions which have no causal effect on the system itself. • Stones ordered by sea: ordering of the stones has no effect at all on the whole system made of the stones and the sea(Castelfranchi, 2001); • Observed functions which have a causal effect on the system. • Desired or not • Have an effect on the system behaviour. • Cause the individual parts to modify their own behaviour. Large-scale adaptive systems - Stefan Dulman

  20. Emergent Phenomena • Engineered systems • Large number of individual components • Large number of interactions occur among these components • Ordering, content and purpose are not necessarily imposed • Behavior of the system is difficult to predict • Use of simulations to predict / tune the result • Negative experiences • Cascading failure effects • Power grid failure • Crowd stampede • Effects: emergent behavior is associated to “bad design” • Rules are put in place to restrain the emergence • Why not use the emergence as a basic mechanism for design? Large-scale adaptive systems - Stefan Dulman

  21. Decentralised Control • Coordination of work without central decisions • Self-organisation mechanisms are (mostly) based on decentralised architectures of information flow • No instruction issued from leaders • Individuals gather information(directly or not) and decide what to do Large-scale adaptive systems - Stefan Dulman

  22. Decentralised Control • Two kinds of engineered systems with decentralised control • Case 1: Large set of autonomous components, pertaining to the same system and providing as a whole expected properties, or functions. • Engineering with emergent functionality in mind • Case 2: Large set of autonomous components, spontaneously interacting with each other, for possibly independent or competing reasons. • No expected emergent global function or properties • In both cases, autonomous components may be • heterogeneous • dynamically joining and leaving the system. Large-scale adaptive systems - Stefan Dulman

  23. Decentralised Control • Example: distributed computer networks • Distribution of computation and decisions among the different components • no need for a central powerful computer; • Increased robustness • the system does not rely on a single node that may fail and crash the whole system; • Better use of network and CPU resources • communication does not occur among a dedicated central node and a large number of components, but locally among the whole set of components; • Flexible schema for communication in highly dynamic systems • Communication with a neighbour instead of with the central entity Large-scale adaptive systems - Stefan Dulman

  24. Self-organisation meets Emergence • Self-organisation without Emergent phenomenon • When there is internal central control • System finds a new organisation fully deducible from a central entity • Ex: Termites under central control of queen • Weak self-organisation • Emergent phenomenon without Self-organisation • No causal effect on the system • No re-organisation • Ex: stones ordered by sea • Physical systems with negative feedback only Large-scale adaptive systems - Stefan Dulman

  25. When Self-organisation meets Emergence • Self-organisation together with emergent phenomenon • Dynamic individual components • Decentralised control • Local interactions among components • Self-organisation is a structure-formationprocess • Strong self-organisation Large-scale adaptive systems - Stefan Dulman

  26. Concepts Self-Organisation Emergent Phenomena Decentralised Control Adaptation Dynamic Change Complexity Large-scale adaptive systems - Stefan Dulman

  27. Adaptation • In living systems – high level • Individual components behave according to genetic programs (rules) tuned by natural selection • Natural selection tunes interactions rules • Natural selection shapes the emergent structures (patterns or function) • Adaptation to long-term environmentalchanges Large-scale adaptive systems - Stefan Dulman

  28. Adaptation • In living systems – local view • Individual components behave autonomously • Local information (“up-to-date”) • Immediate response of system • Adaptation to immediate environmental changes • Adaptation expected for engineeredsystems Large-scale adaptive systems - Stefan Dulman

  29. Dynamic Change • Continual interactions among components • Components join and leave system at any time • Dynamic systems • Ants foraging • Skype system of users • Churn in networks • Dynamic environment • Real world applications Large-scale adaptive systems - Stefan Dulman

  30. Complexity • Individuals organisms use relatively simple behavioural rules • Generated structure and patterns are more complex than the components from which they emerge • Complexity comes from: • Sensitivity to initial conditions (butterfly effect) • Non-linear interactions among components involving amplification and cooperation • Living systems seem to be more complex than non-living ones • Non-living ones subject to physical laws only • Living ones subject to physical laws + behavioural interactions influenced by genetically controlled properties - Camazine et al (1999) Complexity - A guided tour, Melanie Mitchell Large-scale adaptive systems - Stefan Dulman

  31. Complexity in a nutshell Large-scale adaptive systems - Stefan Dulman

  32. Lecture 1 Organization Motivation for adaptive systems Basic concepts and examples Organization issues Large-scale adaptive systems - Stefan Dulman

  33. Course structure Lec.1: Introduction & concepts Lec.2: Adaptation mechanisms Lec.3: Gossip-based algorithms Lec.4: Modeling large scale networks Lec.5: Top-down and bottom-up approaches Lec.6: Design example: tackling mobility Large-scale adaptive systems - Stefan Dulman

  34. Lab information • Practical experiments with NetLogo • 5+1 lab sessions - presence is compulsory! • 5 lab sessions with precise assignments (prepare before!) • Mini-project (lab 6) – delivery 1 week before the exam • Lab topics: • Lab 1: NetLogo tutorial • Lab 2: Diffusion mechanisms • Lab 3: Firefly synchronization • Lab 4: Ant colony routing • Lab 5: ASH clustering scheme • Lab 6: project – static overlays for mobile networks • Assistant: Andrei Pruteanu (a.s.pruteanu@tudelft.nl) Large-scale adaptive systems - Stefan Dulman

  35. Assessment • We will assess: • Activity in the lab (labs 1-5) • Mini-project • Written exam (multiple choice test) • Failing any of the three categories = failed exam • Final mark is composed: • 20% - activity in the lab • 30% - mini project • 50% - written exam Large-scale adaptive systems - Stefan Dulman

  36. Reading Material • Compulsory: 1-2 papers per lecture topic (see lectures & website) • Additional books: • E. Bonabeau, M. Dorigo, and G. ThéraulazSwarm Intelligence: From Natural to Artificial Systems • S. Camazine, J.-L. Deneubourg, Nigel R. F., J. Sneyd, G. Téraulaz, and E.BonabeauSelf-Organisation in Biological Systems • J.H. HollandEmergence – from Chaos to Order • M. WooldridgeAn Introduction to Multi-Agent Systems • L. M. de CastroFundamentals of Natural Computing – Basic Concepts, Algorithms, and Applications Large-scale adaptive systems - Stefan Dulman

  37. Summary • Future of engineering: • Large-scale (mobile) systems • Working in a dynamic environment • We explore alternatives to “classic” design approaches • Adaptive systems showcasing self* properties • Inspiration taken sometimes from nature • Emergent behavior and self-organization as basic blocks • This course focuses on both: • Theory: overview of most prominent techniques – 50% • Practice: 50% of the effort is “hands-on” Large-scale adaptive systems - Stefan Dulman

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