1. A Deployment Algorithm to Achieve both Connectivity and Coverage in Grid Sensor Networks
Diwen Wu, Dongqing Xie, Lupeng Wang
IEEE ICYCS 2008
Presented by : An, Sun Hee
Korea University of Technology and Education
Multimedia Communication and Network Lab.

2. Presentation layout Introduction Preliminary
Deployment algorithm for the connected coverage in local target block
Connected coverage deployment in grid based wireless network
Analysis of the algorithm
Conclusion
MCN Lab.

3. The number of target points
Introduction
Why is a sensor deployment important?
The basic part for the application of the wireless sensor networks.
Direct impact on the performance and life span of the whole network.
Many algorithms has been proposed.
Grid Sensor Networks with target point coverage.
Most algorithm’s time complexity is O(n2).
Present a more efficient heuristic algorithm
for the grid-based target point connected coverage problem.
The number of target points
MCN Lab.

4. Preliminary(1/2) Network model : A grid-based network Assumption
sensing distance = communication distance = the distance between any neighboring vertices = r
The sensors can only be deployed on the position of the gird vertex.
Notation
Sn : the vertices in the grid network with coordinate (x, y).
St : the set of target point (St ⊂ Sn)
MCN Lab.

5. Preliminary(2/2)
Definition 1 : Connected Target Points Coverage in Gird Network
The objective is to find a deployment set Ss
Each target point in St are covered by the sensors in Ss
Any two sensors in Ss can communicate with each other.
Definition 2 : Local Target Block
let, S’t ⊂ St
if. the target points in S’t are connected, and there is no points in St - S’t that is connected with the point in S’t, the points in S′t are called a local target block.
MCN Lab.

6. Deployment algorithm for the connected coverage in local target block(1/7)
Definition 3 : Coverage Coefficient
For point q and its neighboring points,
if there are m target points,
then the coverage coefficient of q is m (m=0, 1, 2, 3).
Choosing coefficient
When deploying sensors, the point with larger choosing coefficient is chosen.
MCN Lab.

7. Deployment algorithm for the connected coverage in local target block(2/7)
CCD algorithm(Sn, St)
Compute the coverage coefficient of each position,
find a target point v following the direction from outside to inside in the network.
The choosing coefficients of the 4 neighbors of v are initialized with the coverage coefficient of v
Choose a position with the largest choosing coefficient to deploy sensor. (By step 3.5)
If 1) there exists a neighboring point q′ of qi such that p, ) qi and q′ are on the same line, and 3) q′ is not covered Then choosing coefficient += 2;
MCN Lab.

8. Deployment algorithm for the connected coverage in local target block(3/7)
If there exists a target point as the neighbor of the chosen position(let the target point be non-target point ) then, modify the coverage coefficient for each neighboring point of the chosen point.
For all the neighboring points of the chosen point, if there exists a point with coverage coefficient larger than 0, the above process is repeated.
MCN Lab.

9. Deployment algorithm for the connected coverage in local target block(4/7)
Theorem 1.
Algorithm CCD(Sn, St) can cover all the target points in the local target block and return the connected coverage, which can be done in time O(|St|).
: Target points
: Sensor
: Local target block
MCN Lab.

10. Deployment algorithm for the connected coverage in local target block(5/7)
Experiment
fixed grid-based wireless network.
50 x 50
Figures
target point :
point with deployed sensor :
non-target point :
MCN Lab.

11. Deployment algorithm for the connected coverage in local target block(6/7)
There are 222 sensors with 11 local target blocks.
MCN Lab.

12. Deployment algorithm for the connected coverage in local target block(7/7)
There are 699 sensor.
MCN Lab.

13. Connected coverage deployment in grid-based wireless network(1/4)
Based on the algorithm CCD
The sensors in a connected local target block are connected.
The sensors in different local target block are not connected.
The remaining problem
How to use least sensors to make all the sensors in the network connected.
The simplest way is to find the shortest path between two blocks.  That is a general idea to solve the problem.
MCN Lab.

14. Connected coverage deployment in grid-based wireless network(2/4)
S : a connected local target block.
Boundary of S : all the points surrounded block S without no sensor deployed
SCC Algorithm(G’)
Find the boundary of S1.
For each boundary point Pi of S1, find all the neighbors of Pi.
If a neighbor of Pi is not a boundary point, set it as a boundary point. Assume the steps needed to extend from one boundary point A to a new boundary point A1 are called the extension depth of A.
1~3 : The above process can be seen as boundary extension.
MCN Lab.

15. Connected coverage deployment in grid-based wireless network(3/4)
At the beginning, the extension depth of boundary point is 0.
Repeat the process until encountering a sensor that is not contained in block S1.
Assume the sensor is B, and it is contained in block S2. Backtrack from point B until to the original boundary.
The shortest path between S1 and S2 is found, Merge S1 and S2, continue to extend boundary from the boundary of S2.
SCC algorithm’s time complexity : O(|Sn|)
MCN Lab.

16. Connected coverage deployment in grid-based wireless network(4/4)
91 sensors are added to make all the sensors connected.
MCN Lab.

17. Analysis of the algorithm(1/3)
The time complexity : O(|St|+|Sn|)
|St| : the number of target point.
|Sn| : the number of points in the network.
Simulation environment
Randomly generate 1000 network of size 5×5 and 6×6.
Use enumeration and interpolation approximation method to find the optimum solution.
Compare the discrepancy between proposed solution and optimum one.
보간(interpolation)이라는 말은, 기존에 알고 있는 특정 지점이나 지역의 속성값을 이용하여 알려지지 않은 지점이나 지역의 속성값을 찾아내는 것을 말한다.
알고 있는 두 점의 값을 이용해서 두 점 사이의 임의 점에서 값을 찾아낼 때 쓰는 방법이기도 하다.
MCN Lab.

18. Analysis of the algorithm(2/3)
The discrepancy in absolute error of the sensors’ number is at most 1.7 and at least 0.76.
The difference in relative error is at most 22.4% and at least 5.5%
MCN Lab.

19. Analysis of the algorithm(3/3)
Proposed algorithm can get better result!
When the number of target points is more larger.
For the network with target point deployment in regular shape.
For the square deployment of target points.  get the optimum solution.
MCN Lab.

20. Conclusion
Work on the connected coverage sensor deployment problem in gird-based network.
Propose an algorithm with time complexity O(|St|+|Sn|).
Lower time complexity.
Proposed algorithm
Just considers how to realize coverage and connectivity
Does not think about the effect of network topology
realize : 달성하다.
MCN Lab.