Mobility Improves Coverage of Sensor Networks

1. Mobility Improves Coverage of Sensor Networks Benyuan Liu*, Peter Brass, Olivier Dousse, Philippe Nain, Don Towsley * Department of Computer Science University of Massachusetts - Lowell

2. Outline • background and motivation • mobility improves coverage • summary and future work

3. What is coverage ? • coverage: quality of surveillance of sensor network • how well sensors cover a region of interest ? • how effective sensor network detect intruders ? • many different measures: area coverage, barrier coverage, detection coverage, etc • important for surveillance sensor net applications • battlefield, infrastructure security

4. Mobile sensor networks • coverage of stationary sensor network intensively studied • sensors can be mobile: mounted on robots or move with environments Q: How does sensor mobility affect coverage?

5. Previous work[Howard 02, Zou04, Wang 04] • sensors move to reach stationary configuration with better area coverage • several approaches proposed, different in how to compute desired locations for sensors (e.g., potential field, virtual force, etc)

6. Our work • different perspective:coverage resulting from continuous movement of sensors 1. mobility increases covered area • stationary sensors: covered area doesn’t change over time • mobile sensors: uncovered area may be covered later, more area covered over time we are interested in area coverage • area covered at specific time instant t • area covered over time interval [0, t) • fraction of time a location is covered

7. Our work 2. mobility improves intrusion detection • stationary sensors: intruder won’t be detected if not move or moves along uncovered path • mobile sensors: may be detected by moving sensors • we are interested in detection time • time before an intruder is first detected • measure how quickly sensors detect intruders • consider stationary and mobile intruders

8. Our work 3. how should sensors and intruder move? • intruder moves to maximize its detection time • sensors minimize the maximum detection time • we are interested in optimal mobility strategies • for both sensors and intruders • game theoretic approach

9. Network model • initial configuration • sensors are deployed uniformly at random • sensor density:  sensing range: r • mobility model • each sensor chooses a random direction [0, 2) according to distribution • speed vs[0, vsmax] according to simple model to obtain insight

10. t Area coverage • area coverage at any given time instant unchanged • uncovered region will be covered, more area will be covered for a time interval [0,t)

11. Tradeoff: covered area and covered time • location alternates between covered and uncovered • uncovered time: covered time fraction of time a point is covered • appropriate for delay-tolerant applications

12. Detection time: stationary intruder Vs • intruder can be detected by moving sensors • detection time: time before first being detected, X • divide sensors into different classes according to direction • time takes to be first hit (detected) by a class i sensor:

13. Detection time: stationary intruder • detection time: smallest hit times among all classes • result: • to guarantee expected detection time smaller than T0 can tradeoff sensor density with speed

14. Mobile intruder: detection time • convert to reference system where intruder is stationary • detection time:

15. Mobile intruder: optimal strategy • target maximizes its lifetime • sensors minimize the maximum detection time a minimax optimization problem

16. Optimal strategy: special cases • sensors: choose direction uniformly in [0, 2) • intruder: stay stationary • intuition: if intruder moves, will hit oncoming sensors sooner • sensors: move in same direction • intruder: moves in same direction with same speed as sensor

17. Optimal strategy: solution ? • sensors choose direction uniformly • target stay stationary • intuition: if not uniform, intruder will move in direction of highest probability density, resulting in longer detection time

18. Summary and future work • define coverage resulting from sensor mobility • derive analytical results to provide insight • future work: • more general mobility and detection model • collaboration among sensors

19. Thank you!