Power Saving Operations in Target Tracking and Surveillance Sensor Networks

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Power Saving Operations in Target Tracking and
Surveillance Sensor Networks

• Chao Gui, Prasant Mohapatra
• Networks Lab. UC. Davis
• Seminar, Jan 2004

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Agenda

• Target tracking and surveillance sensor networks
• Power-saving operations and the network
• Sleep planning during surveillance
• Performance Evaluation

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Multiple Target Tracking (MTT) Problem

• Problem Statement (Sittler-1964, Sastry-2004)
• A varying number of targets
• Arise at random in space and time
• Move with continuous motions
• Persist for a random length of time and disappear
• Positions of targets are sampled at random
  intervals
• Measurements are noisy and
• Detection probability lt 1.0 (missing
  observations)
• False alarms
• Goal For each target, find its track!!!

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Wireless sensor networks

• Wireless sensor node
• power supply
• sensors
• embedded processor
• wireless link
• Many, cheap sensors
• wireless ? easy to install
• intelligent ? collaboration
• low-power ? long lifetime

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Cooperative Tracking with SN

• Advantages
• Easy deployment
• Track multiple targets simultaneously
• Difficulties
• Very limited resources
• Work with local information

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Frisbee A Networks Model for Target Tracking
Applications
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Frisbee A Networks Model for Target Tracking
Applications

• Interesting events happen infrequently, and
  only take place at certain locations.
• Make the sensors sleep during the long interval
  of inactivity.
• When and where event occurs, only a limited zone
  of network is kept in full active state.
• For moving target, the active zone moves along.

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Agenda

• Target tracking and surveillance sensor networks
• Power-saving operations and the network
• Sleep planning during surveillance
• Performance Evaluation

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Work cycle

• Two states for a sensor node
• Surveillance state
• no events of interest in the field, but ready
  to detect any possible occurrences
• Tracking state
• reacts in response to any moving target,
  sensors collaborate in tracking
• Power-saving operations be considered in full
  work cycle.

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Research Issues

• Intuitive and basic scheme
• Sleep, wakeup periodically
• Check for messages and sensing for targets
• If target detected, stop sleeping
• Basic scheme adopted
• Two issues should be considered
• Quality of surveillance
• In-time, in-place transition between two work
  stages

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Problems for Sleeping

• Sleeping reduces the detectability of the network
• When a target first enters the SN field, and all
  the nodes are not in ready-tracking state, how
  long will it travel without exposure to any
  sensor?

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Quality of Surveillance

• QoSurv in general
• Coverage, p-coverage
• Minimum exposure path (MEP)
• Aka. maximum breach path
• QoSurv on moving targets
• Special metrics needed
• Coverage --not necessary for moving object
• MEP --cannot yield direct guideline on sensor
  deployment
• Proposed metric
• How long will a target travel without exposure to
  any sensor?

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QoSurv on Moving Targets
Assumptions (1) No sleeping (2) Non-uniform but
static sensing range (3) Uniform and random
deployment of sensors (4) Area X not fully
covered.
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Approximation of ALUL(X)

• Theorem For any straight line of length l in the
  field, the expected number of intersections the
  line with the disc boundaries is

• Proposition For any straight line of length l,
  and let e be expected number of intersections
  within disc boundaries, l/e approximates ALUL(X).

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Experiment Result
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Agenda

• Target tracking and surveillance sensor networks
• Power-saving operations and the network
• Sleep planning during surveillance
• Performance Evaluation

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Role of Sleep Planning

• QoSurv study guides sensor deployment
• Number of nodes
• Distribution
• Over-deployment of sensor nodes
• Make spare nodes sleep
• Active nodes follow deployment guideline

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Sleep Planning Methods

• Random Independent Sleeping (RIS)
• Independent decide when to wake-up
• Randomized schedule
• Neighbor Collaborative Sleeping (NCS)
• Collaborate on whose turn to be on duty
• Planned Distribution Methods
• Use location info., make the active nodes
  distribute in a planned manner

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Random Independent Sleeping

• Alertness level
• Each node remain active for a percent of total
  time.
• Timeslots
• Within each timeslot, active for aTslot
• Randomized timeslot boundaries

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Neighbor Collaborative Sleeping

• PEAS (Ye-2003)
• Each node initially sleep for random time
• When wakeup, do Probe Environment
• If find working node, decide next sleep time,
  then go sleep
• If not found, become working node till energy
  used up

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Examples
2
Reply
4
1
2
1
Rp
3
3
(a) 2 and 3 are working, 1 probes and starts
(b) 4 probes and 2 replies 4 goes back to
sleep
2
1
6
1
3
3
(c) 2 fails or exhausts energy
(d) 6 probes and replaces 2
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Revised PEAS

• Why revise
• Once starts working, a node does not sleep
• Goal Nodes take turn for duty, balance energy
  consumption among all nodes
• PECAS Probe Environment and Collaborated
  Adaptive Sleeping

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PECAS by example
2
Reply (Ts)
4
1
2
1
Rp
3
3
2 and 3 are working, 1 probes and starts
4 probes and 2 replies with Ts 4 goes back to
sleep for Tse
2
1
4
1
3
3
Ts time later, 2 goes to sleep
4 probes and replaces 2
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Planned Distribution Methods 2-D Mesh

• Only nodes at planned locations are active
• Use 2-D mesh for spatial pattern
• Parameters
• r Sensing range,
• lGGrid spacing

r
lU
lG
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2-D Mesh

• For i-th horizontal line, nodes with x-coordinate
  in range ilG-s, ilGs are active
• Similar for j-th vertical line
• Each line forms a covered stripe of width 2r2 s
• Each uncovered area is approximately a square of
  side length lU
• lUlG-2r-2 s

r
lU
lG
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Deterministic ALUL(X)

• Theorem Let X be the monitored area of size LL.
  The physical deployment of sensors is uniformly
  random distribution of adequate density. The
  distribution of active sensors follows the 2-D
  mesh planned pattern. Then, ALUL(X) is

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Agenda

• Target tracking and surveillance sensor networks
• Power-saving operations and the network
• Sleep planning during surveillance
• Performance Evaluation

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Performance Evaluation
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Performance Evaluation
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Performance Evaluation QoSv
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Performance Evaluation QoSv
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QoSv of mesh with errors
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Performance Evaluation

• Performance Metric
• total energy consumed
• delay of detection

• Simulation Setup
• 800 nodes,
• transmission range 55.9 m,
• sensing range 20m
• target speed 10 m/s

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Performance Evaluation Relative Energy Save
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Performance Evaluation Path Exposure

• Definition Path Exposure
• Summation of networks sensing intensity at each
  point along a path.
• Sensing intensity of a sensor x at a point p is
  defined as S(x,p) 1/ x, p4.

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Performance Evaluation Path Exposure
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Questions, remarks?
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References

• S. Tilak, N.B. Abu-Ghazaleh, W. Heinzelman, A
  Taxonomy of Wireless Micro-Sensor Network
  Models, Mobile Computing and Communications
  Review, Vol. 6, No. 2.
• A. Cerpa, J. Elson, M. Hamilton, J. Zhao,
  Habitat Monitoring Application Driver for
  Wireless Communications Technology, First ACM
  Sigcomm Workshop on Data Communications in Latin
  America and the Caribbean, Apr. 2001
• K. Mechitov, S. Sundresh, Y. Kwon, G. Agha,
  Cooperative Tracking with Binary-Detection
  Sensor Networks, Technical Report
  UIUCDCS-R-2003-2379, Computer Science, UIUC,
  Sept. 2003