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University of Virginia Full Life Cycle Analysis for Wireless Sensor Networks January 10, 2007 Computer Science University of Virginia Jack Stankovic.

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Presentation on theme: "University of Virginia Full Life Cycle Analysis for Wireless Sensor Networks January 10, 2007 Computer Science University of Virginia Jack Stankovic."— Presentation transcript:

1 University of Virginia Full Life Cycle Analysis for Wireless Sensor Networks January 10, 2007 Computer Science University of Virginia Jack Stankovic

2 University of Virginia Main Themes of Talk Require design time analysis to obtain approximate system design – do this with few assumptions Redo analysis as a function of subsequent design choices –Specific routing protocol Analysis of various types required at all phases of system design, implementation, and operation Require a tool/framework for combining multi-stage analysis

3 University of Virginia VigilNet - Power Aware Surveillance Acoustic Magnetometer Four 90 degree motion sensors XSM motes - Crossbow ACM TOSN, Feb. 2006

4 University of Virginia 1. An unmanned plane (UAV) deploys motes 2. Motes establish an sensor network with power management 3.Sensor network detects vehicles and wakes up the sensor nodes Zzz... Energy Efficient Surveillance System Sentry

5 University of Virginia Tripwire-based Surveillance Self-organize (partition) sensor network into multiple sections (one per base station). Turn off all the nodes in dormant sections. Apply sentry-based power management in tripwire sections Flexible scheduling, sections rotate to balance energy. Road Dormant Active DormantActive Dormant

6 University of Virginia Sentry Duty-Cycle Scheduling A common period p and duty-cycle β is chosen for all sentries, while starting times T start are randomly selected Non-sentries Sentries Target Trace A B C D E A B C D E t t t t t Awake Sleeping p02p

7 University of Virginia VigilNet Architecture

8 University of Virginia Life Cycle Analysis Design Time –Analytical Programming Time –Execution time, memory, delays, … Debugging Time –Operational, fix bugs, race conditions Field Testing Time –Overhear, replay System Lifetime –Validation services

9 University of Virginia ANDES Extensible Design Tool –Model and analyze WSN “early” –Iterate to obtain final configuration Integrate analysis into a design tool - Plug-ins –Target tracking analysis –Communication schedulability analysis –… Extend AADL/OSATE framework –Used extensively for real-time and embedded systems –CMU/SEI

10 University of Virginia Design Time Performance Attributes –Lifetime –Sensing coverage –Communication Capacity –Reliability –QoS –Security System Parameters –Number of nodes –Density –Duty cycle –Sensing Range –Communication range –Bandwidth

11 University of Virginia Example - Tracking Analysis

12 University of Virginia Tracking Analysis First Level of Analysis –Probability of detection –Average detection delay –Density d –Duty cycle b –Period T –Sensing range R –Length of Path L –Speed of target v (stationary, slow, fast) –Impact on lifetime

13 University of Virginia Obtain Probability of Detection 0 T l/v t βTβT βT+l/v Probability of detection (βT+l/v ) /T R l target locus Node l/v Time interval when the target is in the sensing area βTβT Time interval when the node is awake in one period

14 University of Virginia Consider All Possible Locations R L l A For a fast target with velocity v R (x,y) target locus

15 University of Virginia Formulas for Detection Delay Expected Detection Delay for Fast Targets: Expected Detection Delay for Slow Targets: where * DCOSS paper

16 University of Virginia Expected Delay vs. β Minimum energy gives 1.3s detection delay

17 University of Virginia Realistic Sensing Areas Formulas Validated What do real sensing areas look like?

18 University of Virginia Real-Time Communication Analysis Next level of analysis –Are expected end-to-end data flows going to meet their deadlines? –Fn(bandwidth, deadlines, periods, workloads) –Impact on lifetime

19 University of Virginia Schedulability Analysis – Example Stream Message Size PeriodDeadline Start time 12000b100ms1000ms0 2200b20ms100ms0 340b10ms 50ms0 Interference range3m Radio range1m Stream specification Communication parameters Network topology Result: Schedulable Communication Link from node 1 to 2 is assigned to stream 1 at time slot 1 Communication Link from node 3 to 5 is assigned to stream 3 at time slot 1

20 University of Virginia RT Scheduling Analysis Analysis includes –The impact of interference –Streams’ time constraints –Multi-hop communication Assumptions –Perfect collision-free MAC protocol –Fixed routing –Constant communication and interference range –No transmission failure

21 University of Virginia Solution - Exact Characterization Analogous to real-time scheduling theory Prioritize streams (velocity) Schedule stream 1 Schedule stream 2 assuming stream 1 exists –Account for time, BW and interference Keep adding streams until –All streams successfully scheduled –All streams up to stream X successfully scheduled

22 University of Virginia Analogy of Schedulability Problem to Cylinder Packing

23 University of Virginia Implementation of Analysis Can be very general

24 University of Virginia 1. An unmanned plane (UAV) deploys motes 2. Motes establish an sensor network with power management 3.Sensor network detects vehicles and wakes up the sensor nodes Zzz... VigilNet Surveillance System Sentry

25 University of Virginia Main Idea of EnviroLog A distributed service that achieves repeatability via asynchronous event recording and replay Input Log modules Target modules Output Enviro- Log Flash Record Stage

26 University of Virginia Main Idea of EnviroLog A distributed service that achieves repeatability via asynchronous event recording and replay Input Log modules Target modules Output Enviro- Log Flash Replay Stage

27 University of Virginia Uses of EnviroLog System evaluation –Suite of real tests recorded and replayed Debugging –Exact same tests Protocol comparison in real setting –Exact same tests Parameter tuning –Exact same tests Wider testing than possible with physical system (e.g., speed up capability exists) Valuable for rare, unsafe or hard to reproduce events –Fire, explosion, …

28 University of Virginia Summary Require Initial Analysis to Approximate Design Parameters Refine Based on Design Decisions – analysis accounts for those decisions Validation of the Early Analysis via Empirical Data Value of AADL basic features/analysis Integration among Life Cycle Analyses –A comprehensive and consistent toolkit

29 University of Virginia Acknowledgements VigilNet – large team at UVA (Tian He, …) ANDES – (Vibha Prasad, …) Tracking Analysis – (Ting Yan, …) Envirolog – (Liqian Luo, …) Papers available on each of these topics


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