Monitoring applications are one of the main usages of wireless sensor networks, where the sensor nodes are responsible to report any event of interest in the monitoring area. Due to their limited energy storage, the nodes are prone to fail, which may lead to network partitioning problem. To cope with this problem, the number of deployed sensor nodes in an area is more than the required quantity. The challenge is to turn on a minimal number of nodes to preserve network connectivity and area coverage. In this paper, we apply computational geometry techniques to introduce a new 2-phase algorithm, called Delaunay Based Connected Cover (DBCC), to find a connected cover in an omnidirectional wireless sensor network. In the first phase, the Delaunay triangulation of all sensors is computed and a minimal number of sensors is selected to ensure the coverage of the region. In the second phase, connectivity of the nodes is ensured. The devised method is simulated by NS2 and is compared with two well-known algorithms, CCP and OGDC. For the case, where the communication and the coverage radii are equal, our method requires 23% and 45% fewer nodes compared to the aforementioned methods, respectively. In the second simulation case, the communication radius is set to 1.5 times of the coverage radius. The results demonstrate that DBCC chooses 14% and 34% fewer nodes, respectively.

1. DELAUNAY BASED TWO-PHASE
ALGORITHM FOR CONNECTED
COVER IN WSNS
Maryam Tahmasbi
Hadi Tabatabaee Malazi
Fahimeh Eltejaei

2. Connected cover

3. A connected cover
Delaunay based two-phase algorithm for
connected cover in WSNs

4. Related work
Coverage Configuration Protocol (CCP) that results different
degrees of coverage and also maintains the communication
connectivity.
• The coverage can imply connectivity only when sensors’
communication ranges are not less than twice of their
sensing ranges (2Rs ≤ Rc).
• The desired connectivity of boundary sensing nodes are
equal to the degree of coverage.
• The desired connectivity of interior nodes are twice the
degree of coverage.
• Shortcomings of the method is that it does not guarantee
network connectivity for the case where Rc < 2Rs.
Delaunay based two-phase algorithm for
connected cover in WSNs

5. Related work
• Zhang and Hou in [10] proved that if the
communication range is 3 times of the sensing
range, the area coverage will result network
connectivity.
• They proposed an algorithm where a sensor is
activated if the coverage overlap of that sensor with
other sensors is minimum.
Delaunay based two-phase algorithm for
connected cover in WSNs

6. Delaunay triangulation
• A Delaunay triangulation for a
set of n points in the plane is a
triangulation such that the
circumcircle of every triangle
Contains no points inside it.
Delaunay based two-phase algorithm for
connected cover in WSNs

7. DBCC algorithm
First phase: coverage phase:
• Building a Delaunay triangulation G on sensors.
• Starting from an active node (sensor), visiting all
nodes using BFS algorithm, activating each sensor if
it is not covered by a neighboring node.
Second phase: connectivity phase.
• Finding the connected components.
• Selecting pairs of connected components with
smallest distance in G.
• Connect two components with a shortest path in G.
Delaunay based two-phase algorithm for
connected cover in WSNs

8. Delaunay based two-phase algorithm for
connected cover in WSNs

9. Delaunay based two-phase algorithm for
connected cover in WSNs

10. Computational Complexity
• 1st Phase:
• 2nd Phase:
Delaunay based two-phase algorithm for
connected cover in WSNs

11. Experimental study
• Randomly placed sensors in a rectangular area of
400 x 400 m2.
• Sensing range (Rs) = 50 m
• Communication range (Rc) = from 40 to 100 m.
• The number of sensors varies from 160 to 320
Delaunay based two-phase algorithm for
connected cover in WSNs

12. The number of active sensors in different
range ratio.
Delaunay based two-phase algorithm for
connectedcover in WSNs

13. The number of active nodes when
communication range varies
Rs = 50 m
50 m < tr<70 m
Delaunay based two-phase algorithm for
connectedcover in WSNs

14. The execution time with different
communication range for Rs=50 m
Delaunay based two-phase algorithm for
connectedcover in WSNs

15. Comparison
• We compared DBCC algorithm with CCP and OGDC.
• Number of sensors: from 100 to 700
• A rectangular area of 400 x 400 m2
• Rs=50 m
• Rc= 1 , 1.5 and 2 times Rs
Delaunay based two-phase algorithm for
connected cover in WSNs
The experiments show that the number of active sensors in DBCC
in average is 23% less than CCP and 45% less than OGDC.

16. Comparing the number of active nodes in
different algorithms, when Rc = 50m
Delaunay based two-phase algorithm for
connectedcover in WSNs

17. Comparing the number of active nodes in
different algorithms when Rc = 75m
Delaunay based two-phase algorithm for
connectedcover in WSNs
when the communication range is 1.5 times of the sensing rang,
the number of sensors in DBCC is 15% less than CCP and 20% less
than OGDC in average.

18. Comparing the number of active nodes in
different algorithms when Rc = 100m
Delaunay based two-phase algorithm for
connectedcover in WSNs

19. Conclusion
• we developed a new two phase algorithm (DBCC) for
finding connected cover in WSNs.
• The main idea was to use Delaunay triangulation for
navigating through the sensor field, then using BFS
algorithm to select next sensor.
• Simulations showed that DBCC performs better in
cases when coverage does not guarantee the
connectivity.
Delaunay based two-phase algorithm for
connected cover in WSNs

20. Thank you for your attention.
Any Questions?
Delaunay based two-phase algorithm for
connectedcover in WSNs