Clustering is commonly used for data routing in wireless sensor networks. This document proposes using compressive sensing (CS) with clustering to further reduce data transmissions. Simulation results show that clustering with hybrid CS can significantly reduce transmissions compared to clustering without CS, shortest path tree routing without CS, and shortest path tree routing with CS. Specifically, when the compressive ratio is 10, clustering with hybrid CS reduced transmissions by 60% compared to clustering without CS and 50% compared to the other methods. When the ratio is 5, reductions were 50%, 40%, and 20% respectively. Thus the proposed method of using CS with clustering minimizes data and helps maximize the lifetime of resource-constrained sensor networks.

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.