clustering in wireless sensor networks with compressive sensing

CLUSTERING IN WIRELESS SENSOR NETWORKS USING

COMPRESSIVE SENSING

Wireless sensor network

• Sensor nodes distributed for observing physical and environmental conditions

Clustering for data routing•Clustering is a data aggregation method

Clustering in wireless sensor networks

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.

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

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

Clustering with Hybrid CS

Simulation of the project

TOPOLOGY FORMATION

CLUSTER FORMATION

SINK

2

0 m

10 m

Clustering in simulationCLUSTER HEAD’S

SINK AT (0,0)

ResultsWHEN THE COMPRESSIVE RATIO IS 10

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

WHEN COMPRESSIVE RATIO IS 5

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

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.