# Differentiated Surveillance for Sensor Networks

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```					Differentiated Surveillance for
Sensor Networks
Ting Yan, Tian He, John A. Stankovic

CS294-1
Jonathan Hui
November 20, 2003
Idea
   Exploit node
density/redundancy
to maximize
effective network
   Degree of coverage
matters!
   Sensing constraints
   Fault tolerance

2
Assumptions
   Static placement
   Localization
   Time Synchronization
   For simplicity of describing protocol?
   Nodes on 2D plane
   Communication range > 2r
3
Basic Protocol
     Initialization Phase
   Localization, Time Sync, Determine
Working Schedule (T, Ref, Tfront, Tend)
     Sensing Phase
   Nodes power on and off based on working
schedule
Round 0 (T)     Round 1 (T)               Round i (T)
Ref             Ref                       Ref

Tfront   Tend   Tfront   Tend             Tfront   Tend
t

Init Phase                                 Sensing Phase                       4
Basic Protocol
Determining Working Schedule

   Goal: Each node determines its own
working schedule such that all points
within sensor coverage are covered for
all time.
   Approach: Represent sensor coverage
with grid of points

5
Basic Protocol
Determining Working Schedule

   Reference Point Scheduling Algorithm
   Randomly choose Ref from [0, T) and broadcast to
all nodes within 2r.
   For each discrete point
   Order neighboring Ref times and calculate
     Tfront = [Ref(i)-Ref(i-1)]/2
     Tend = [Ref(i+1)-Ref(i)]/2
   Final schedule = union of schedules for all points
RefC RefA             RefB
Point 1                                          RefC RefA          RefB
Node A:
RefD      RefA   RefE                 RefD         RefE
Point 2
6
Enhanced Protocol
with Differentiation

    Working schedule for a desired                     Example (a = 1)
RefB   RefC
RefA
coverage of degree a.
   (T, Ref, Tfront, Tend, a)                       A
   Working period defined as:                      B
   Power On:    T  i  Ref  T front  a
C
   Power Off:   T  i  Ref  Tend  a

Example (a = 2)                                     Example (a = 3)
RefA                  RefB   RefC                   RefA            RefB   RefC

A                                                   A
B                                                   B
C                                                   C          Uh-Oh!
7
Design Issues
   Possible blind spots with discrete points
   Choose points within sensing range conservatively
   Offset in time synchronization
   Power on (off) slightly earlier (later)
   Irregular sensing regions
   Okay, as long as sensing regions of neighboring nodes are
known
   But also requires knowledge of orientation
   Fault Tolerance
   Awake nodes use heartbeat messages to detect failed nodes
   If a node fails, wakeup all nodes within 2r and reschedule.
   What if communication range < 2r?
8
Extensions and Optimizations
   Second Pass Optimization
   After determining working schedule,
broadcast schedule to all nodes within 2r.
   The node which has the longest schedule:
   Minimize Tfront and Tend while maintaining
sensing guarantee
   Done when every node has recalculated
schedule or when no more can be done.

9
Extensions and Optimizations
   Multi-Round Extension for Energy
Balance
   Calculate M schedules each with different
Ref values during Init Phase.
   Rotate schedules during Sensing Phase.
RefC RefA RefB    RefB   RefC RefA RefA RefB   RefCRefA     RefC       RefB

A
B
C
10
Schedule 1         Schedule 2         Schedule 3         Schedule 4
Evaluation
   Simulation parameters
   Nodes distributed randomly with uniform
distribution in 160mX160m field.
   Results taken from center 140mX140m to avoid
edge effects
   Sensing range = 10m
   Communication range = 25m
   Ideal conditions
   Fault tolerance included?
11
Evaluation
   Total energy
consumption nearly
constant with changes
in density.

   Variation in total energy
consumed decreases
with greater densities.
   What’s happening with
approach?
12
Evaluation
   Half-life increases
linearly as density
increases.

   Coverage
provided for
longer period of
time.

13
Evaluation
   Energy consumption
increases linearly with
different degrees.
   Energy consumption
constant with different
densities.

   Degree of coverage
provided >= a.
   a only guarantees a
lower bound.

14
   Localized algorithm?
   But still requires time synchronization and doesn’t support
mobility
   Inflexible
   mobility not supported, schedules are fixed
   No notion of the “goodness” of a node
   Nodes that have more energy should take up a larger
portion of the working schedule
   Difficult to reliably broadcast Ref values to all 2r
neighbors in a dense network
   Only have one chance to get it right!
   Worse in cases where communication range < 2r (i.e.
acoustic sensors)

15
   Working schedules determined without taking other
schedules and protocols into account
   How does it affect other protocols (i.e. TDMA)?
   Comparison to Sponsored Coverage unfair
   Sponsored Coverage supports fault tolerance, limited
   Ability to specify degree of coverage
   But current algorithm doesn’t correctly guarantee with a >
2!
   Fault tolerance relies on communication range > 2r
for heartbeat messages

16
Conclusion
   Pros
balance
   Specify a degree of coverage
   Cons
   No upper bound on degree estimation
   Inflexible
   Static working schedule, static nodes, time
synchronization, reliable communication

17

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