1. Wireless Sensor Networks Summary Professor Jack Stankovic Department of Computer Science University of Virginia

2. Outline WSN – its niche Applications revisited Fundamentals – early in research Some Intriguing Concepts in this field Future Research Areas

3. WSN – Its Niche Distributed Computing –Load balancing, group management, distributed OS, middleware, network protocols, … Sensor Networks (wired or powerful wireless) –Submarines, automated factories, fleets of ships, … –Real-time systems –DSP Radio Communications (Wireless) –Radio signals Combine all three with significant constraints

4. WSN – Its Niche Mobile Ad Hoc Networks (MANET) –Laptops –Single hop? Distributed Embedded Systems of Appliances –Ubicomp –Products with embedded sensors/computing (toasters, refrigerators, air conditioning, etc.) –RFIDs

5. WSN – Its Niche Dust to grids –Dust, motes, heterogeneous sensor nets, Internet, the grid Cell phones (increasing capabilities) –Connect to WSNs (act as base stations) –Connect to products with embedded computing –Connect to Internet –Connect to Grid –Oh yeah –> also make phone calls

6. 1 Billion Node WSN Future World: –Every Cell Phone has pollution sensor and reports readings periodically –Add other sensors –Universal device?

7. How the Problems Change Environment –connect to physical environment (large numbers, dense, real- time) –faulty, highly dynamic, non-deterministic –wireless – contention, irregular patterns –power management critical Network –structure is dynamically changing –sporadic connectivity –new resources entering/leaving –large amounts of redundancy –self-configure/re-configure –individual nodes are unimportant - route/query to AREA

8. How the Problems Change OS/Middleware –manage aggregate performance Control the system to achieve required emerging behavior How do we know it works? –self-organizing (self-*) –team formation with fuzzy membership –manage power/mobility/real-time/security tradeoffs –geographical/location based (spatial) –real-time/real world (temporal) –data centric –support new (language) paradigms

9. Implications Fundamental Assumptions underlying distributed systems technology has changed –wired => wireless (limited range, high error rates) –unlimited power => minimize power –Non-real-time => real-time –fixed set of resources => resources being added/deleted –each node important => aggregate performance New solutions necessary

10. Applications Passive sensing of environment/data collection Same as above with actuators Active tracking/target discrimination Degrees of mobility Interface with the Internet Handheld PDAs/laptops (seemless integration) Heterogeneity Placed versus ad hoc deployment Any killer apps? Any wild new apps?

11. Function(Cost) 200 nodes at $100 ea. -> $20,000 20,000 nodes at $1 ea. -> $20,000 20,000 nodes at.10 ea. -> $2,000

12. One Architecture Sensors Actuators CPUs/Memory Omni-dir. Radio

13. Second Architecture Fixed Deployment (grid, mesh, …)

14. Taxonomy HW Capabilities Application Requirements Software/Middleware

15. Fundamentals What is truly fundamental about WSN? –Power limitations? Solar cells/close down for a time to recharge/plug into wall socket, etc. Probably a major problem for a long time and for many applications –Cpu/memory capacity? New platforms are being built –Large Scale? Not necessary for all systems –Long Lifetimes?

16. Fundamentals Interact with the environment – sensing –Consider all the realities of sensing … –Sensor fusion/data aggregation –False Alarm Processing Multi-hop wireless radio communication –Consider all the realities of radio comm. –Asymmetry, lost messages, nodes move, nodes sleep or die, etc. Ratio of communication/sensing ranges

17. Radio Model in Evaluation Radio Model DOI = Degree of Irregularity DOI = 0.05 DOI = 0.2

18. Communication A funny thing happened on the way to the destination –Lost packet –Congestion (long delay) –Lost node –Eavesdropped on –Corrupted –Changed on purpose –Cycle –Interfered with by other radio transmissions

19. Sensing versus Communication Sensing/communication range ratio Sensing/communication/power tradeoffs Sensing Range Communication Range What if the opposite? Required degree of coverage?

20. Fundamentals Self-configure, self-manage, self-heal Self-awareness –Space (location/geography), time, energy, dynamics, security, reliability Self-calibrate Self-* Unattended operation (completely or almost completely) -> difficult physical accessibility Self-stabilizing algorithms

21. Localization : A mechanism for discovering spatial relationships among objects Fundamentals

22. Localization Node Target Discovery Service Robust, secure, Fn(many parameters)

23. Fundamentals Aggregate Behavior – biological metaphors Simple decentralized algorithms (localized behavior) –Epidemic/virus type algorithms –Randomized algorithms –Develop local rules that yield desired macroscopic behavior Lazy behavior (fast dynamics)

24. Epidemic Algorithms Final state –Backward links The flood extends towards the source –Stragglers MAC-level collisions –High clustering Most nodes have few descendants A significant few have many children

25. Fundamentals - Scale 20 ---- 200 ---- 2000 ---- 20,000 Flooding Acknowledgements Information into and out of system State of system Management/Maintenance

26. Fundamentals Uncertainty –Packets delivered –Irregular communication range –Faults –False alarms (and sensor processing) –Changing environment –Changing topology –Resources entering/leaving –Power degrading

27. Fundamentals - Events Size of targets/events (point/area) Discrete versus continuous Probabilistic Fire X Explosion

28. Fundamentals Group Management and Consensus

29. Example: Consensus Classical consensus: all correct processes agree on one value –No power constraints –No real-time constraints –Does not scale well to dense networks –Approximate agreement (some work here) - on sets of values (physical quantities) New Solutions ?

30. New Concept of Consensus Termination: every correct processor eventually decides some value Uniform Agreement: no two processors decide differently Group Membership: join/leave - everyone knows who is in the group Termination: “at least n” correct processors decide some value by time t Group Agreement: at least n processors decide the same value within epsilon Area/Function Membership: join/leave an area or by function Classical New Definitions

31. Examples: Tracking and Map Regions Base Station

32. What’s Hard Multiple targets Crossing targets False Alarms –Depends on (changing) environment, sensors, confidence tradeoffs, noise, lost messages, …) Speed of targets Uniqueness of targets Classify targets Proper abstractions Save power/minimize communication

33. Fundamentals - Security What is the single most important issue that could prevent WSNs from wide scale deployment? –Security –2 nd issue -> Privacy At application level –Authenticity and integrity Security of each service (examples) –Routing: non-secure if a single node is captured! Eavesdrop or change message Flood Insidious unintended consequences of collecting data –Monitor oceans for fish migration (data mine location of submarine fleet)

34. Fundamentals - Analysis Control Theory Markov Processes Real-time Schedulability Analysis Optimization Theory Graph Theory (Random Graphs?) Information Theory Phase Transitions Guarantee Quality of Service Diffusion Theory?

35. Intriguing Concepts Space (geography/location) –GF Time (deadlines/periods/event lifetime/power lifetime) –SPEED, clock sync, power management Aggregate Behavior (emerges versus controls)

36. Velocity (Spatio-Temporal) USE VELOCITY

37. Bound Errors End-to-end Real-time Collisions Congestion Destination Source Error Propagates Race Ahead

38. Behavior Flooding – stragglers Epidemic algorithms and phase transitions Global routing behavior – more emerged than controlled

39. Feedback Control (FC) 2 3 5 9 10 7 Delay Boo 4 11 6 1 3 12 Packet 1 Beacon Packet 2 SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks.

40. Use FC – Packet Aggregation Adaptive choice of N Take into account the output Queue delay Delay is used to adjust the output queue push rate and degree of aggregation

41. Integrated Solutions Routing solutions must be –Power aware –Robust to lost messages, dead motes, voids –Provide real-time QoS –Robust to communication range variations and asymmetries –Handle moving end points –Scale –Secure

42. Interactions Insidious interactions –Assume high density with many motes turned off to enable long system lifetime –Turn on when activity happens –Then too many are active with many collisions and poor response

43. Future Research Directions New platforms/architectures Higher level middleware Application level semantics –E.g., N events in nursing home implies patient is OK Aggregate behavior (algorithms, control, predict…) Systems implementations/applications Systems of systems (pervasive computing)

44. Future Directions of Research Real-Time Security Privacy Analysis Techniques and Tools Mobility View as Storage Systems Programming Paradigms Localization

45. Future Directions of Research Data Association Sensor Fusion Classification Turn-Key System Autonomic WSN