1. University of Amsterdam, Distributed Systems1 Distributed Systems DOAS Marinus Maris

2. University of Amsterdam, Distributed Systems2 Centralized versus distributed systems CentralizedDistributed device Host computer device Host computer device

3. University of Amsterdam, Distributed Systems3 Intelligent Distributed Systems NID Host computer

4. University of Amsterdam, Distributed Systems4 Networked Intelligent Devices Every sensor and actuator is equipped with local intelligence and a network connection NIDs can: –Analayze their environment –Communicate –Negotiate –Take decisions and actions autonomously

5. University of Amsterdam, Distributed Systems5 Embedded Systems Smart Sensors Actuators Networks Algorithms NIDs To create distributed NID networks, synergie between technologies is required NIDs

6. University of Amsterdam, Distributed Systems6 Typical NID architecture

7. University of Amsterdam, Distributed Systems7 Typical Distributed System Architecture central

8. University of Amsterdam, Distributed Systems8 Why distributed? Distributed monitoring and control enables: Local intelligence, so fast and appropriate response Good scalability Hierarchical decomposition into sub-control groups. This lowers the computational complexity since the groups need only partial knowledge Sub-groups can be optimized for space and (response) time Graceful degradation. Failure of one device won’t lead to total system failure.

9. University of Amsterdam, Distributed Systems9 Typical use: Robust Control Networks for complex systems ships process industry offshore Increase the robustness of such control systems Improve the reaction time in case of calamities Reduce required manpower for emergency recovery

10. University of Amsterdam, Distributed Systems10 (Some) Distributed Intelligence Methods Rule Based Fuzzy Logic Neural Networks Bayesian Networks Gradient method Demand-supply method

11. University of Amsterdam, Distributed Systems11 Example case: Chilled Water System on a Ship

12. University of Amsterdam, Distributed Systems12 Decomposition into subsystems

13. University of Amsterdam, Distributed Systems13 Assign states to the subsystems (voorbeelden)

14. University of Amsterdam, Distributed Systems14 Network Architecture

15. University of Amsterdam, Distributed Systems15 Method 1: Rule-based Knowledge of system is represented in rules, such as: – if pipe leaks then close valves Rules are simple however… Difficult to maintain So make a hierarchy of rules (e.g. define for each subsystem a small set of rules): – If koelmiddel1 defect then close it and open cross-over

16. University of Amsterdam, Distributed Systems16 2. Bayesian Network (voor probleem-analyse)

17. University of Amsterdam, Distributed Systems17 Adding evidence: “kleppenKW gesloten”

18. University of Amsterdam, Distributed Systems18 Adding evidence: “CoolingVIT1”=false Waar zit nu de grootste kans op het defect

19. University of Amsterdam, Distributed Systems19 3. Gradient Method: Determines the shortest path in a network (in this case pipes) Scales very well Cannot exploit multiple sources for cooling

20. University of Amsterdam, Distributed Systems20 4. Demand Supply Control Method Free market principle Negotiation between suppliers and demanders Cooling is the product Priority determines which party will deliver the product Scales well Can exploit multiple sources Due to the inertia of the medium (water) the lack of cooling may be discovered rather late

21. University of Amsterdam, Distributed Systems21 Comparison Methods (chilled water system)

22. University of Amsterdam, Distributed Systems22 Hybrid Approach All methods have their own specific advantages and drawbacks, so use a hybrid approach, for example:

23. University of Amsterdam, Distributed Systems23 Other case: Sensor networks MICA Motes/Dots Developed by U.C. Berkeley & Crossbow for research They posses a microprocessor, bi-directional radiolink Can be extended with several (MEMS) sensors Distributed operating system, TinyOS

24. University of Amsterdam, Distributed Systems24 Voorbeeld: Gebouw beveiliging “Compound security”

25. University of Amsterdam, Distributed Systems25 Compound Security, User-interface Node is (nog) niet actief Node niet meer actief Node actief, geen detectie Node actief, detectie Node actief, Geen detectie, voorheen wel detectie Mogelijke toestanden:

26. University of Amsterdam, Distributed Systems26 Distributed Systems, general advantages Scalable Quick response times Lower communication bandwidth required Robust (graceful degradation) Autonomous decision making through negotiation Reduces false alarm rate through combining different sensor information Low power requirements Cheap Quick and easy installation (sensors can be thrown out)

27. University of Amsterdam, Distributed Systems27 Typical disadvantages / challenges Localization Ad-hoc networking Sensor-fusion Security Lower power More computing power required per node Communication and processing are more complex The intelligence layer

28. University of Amsterdam, Distributed Systems28 A possible future….