Clustering in wireless sensor networks with compressive sensing.

1. CLUSTERING IN WIRELESS SENSOR
NETWORKS USING COMPRESSIVE
SENSING

2. Wireless sensor network
• Sensor nodes distributed for observing
physical and environmental conditions

3. Clustering for data routing
•Clustering is a data aggregation method
Clustering in wireless sensor networks

4. Compressive sensing
• Mathematical technique
• Works on the logic of :
‘information’ bandwidth<‘total’ bandwidth
• States that it is possible to acquire same
amount of data from fewer measurements
than we take conventionally.
• Applicable as WSN data is largely of sparse
nature.

5. Data
sensed by
the sensor
nodes
M<<N
samples are
transmitted
Y=φx projections
are transmitted Obtain x by using
l-1 minimalization
Accurate
recovery of
signals
Compressive ratio = M/N

6. Analysis and comparison
We compare routing using
• Clustering with no CS
• clustering with Hybrid CS
• SPT with no CS
• SPT with hybrid CS
Parameters of comparison
• No. of transmissions vs. no. of nodes
• Reduction ratio of transmissions

7. Clustering with Hybrid CS

8. Simulation of the project
TOPOLOGY FORMATION
CLUSTER FORMATION
SINK
20m
10 m

9. Clustering in simulation
CLUSTER HEAD’S
SINK AT (0,0)

10. Results
WHEN THE COMPRESSIVE RATIO IS 10

11. if no. of measurements =1/10 (no. of nodes )
Reduction Ratio Method 1 Method 2
60 Clustering with
hybrid CS
Clustering
without CS
50 Clustering with
hybrid CS
SPT without CS
30 Clustering with
hybrid CS
SPT with Hybrid
CS

12. WHEN COMPRESSIVE RATIO IS 5

13. if no. of measurements =1/5(no. of nodes )
Reduction Ratio Method 1 Method 2
50 Clustering with
hybrid CS
Clustering
without CS
40 Clustering with
hybrid CS
SPT without CS
20 Clustering with
hybrid CS
SPT with Hybrid
CS

14. Results
• Our method of using CS with clustering in
WSN can significantly reduce data
transmissions compared with conventional
data collection methods of Clustering without
CS,SPT without CS,SPT with CS.
• Using clustering with hybrid CS minimize data
transmissions and help maximize lifetime of
network with the resource constrained sensor
nodes.