Simulation of Sensor Clustering in WBAN Networks

Project by:Arundale R.

M.Sc. Computer ScienceCentre for Distance Education

Anna University

Roll No.: 1314MCS0048Reg. No.: 75713200003

Guided by:Mr. Kanakasabapathi. V.

Wireless Body Area NetworksIntroduction

http://zionkerala.blogspot.in/2015/01/wireless-body-area-network-future.html

Wireless Body Area Networks (WBAN) were primarily developed to address the need for continuously monitoring people (medical patients) suffering from chronic heart diseases, diabetes and such other critical medical conditions.

The IEEE standard (802.15.6) proposes the PHY, MAC and network layer for transmission of data. It also proposes two network topologies viz. One-hop star network and cluster based transmission.

WBAN Constraints

Sensors are battery operated. So,

● Battery capacity is limited

● Transmission range is limited

Chestor Simpson, “Characteristics of Re-chargeable batteries”, Texas Instruments, 2000.

Proposed System

Develop a simulation environment of sensor nodes to visualize a WBAN and demonstrate how energy consumption can be optimized by finding the shortest route to the base station.

The base station can make long range radio transmissions to reach a node anywhere within the sensor network. However in order for messages to travel from a sensor node to the base station, the message has to hop from node to node in order to maximise the energy conservation.

Visualization of proposed system

Base Station

CH1S1.1

S1.2

S1.3

S1.4

CH2S2.1

S2.2

S2.3

S2.4

CH3S3.1

S3.2

S3.3

S3.4

Healthcare provider

Internet

CH : Cluster Header (or) Sensor node

S : sensor

Dotted arrows indicate alternate route to reach

base station by more than one hop.Cluster 3

Cluster 2

Cluster 1

Data flow diagram

AdministratorCreate Base

Station and SensorClusters,

Assign location,Voltage level

Start Simulation

Loadconfiguration

Assigntransmission

Intervals,Thresholds forCharging and

distance

Setup BaseStation and

Sensor nodepositions

ViewPerformance

statistics

Find shortestPath usingDijkstra'sAlgorithm

Choose firstnode

SimulateBattery

discharge

Simulate datatransmission

from node

Logs

Configuration

Find all pathsto Base StationTransmit

data

Choose nextnode

System Block diagram

Simulator JRE

SwingFrontend

GUI

Logs

SensorNodes

BaseStation

Dijkstra'sShortest

path

Pathfinder

Configload /save

Batterycharge /

dischargeUser

Class Diagram

Dijkstra's Algorithm

Source: Wikipedia

Animation

(1)

(2)

(3)

Implementation (Screenshots)

(1) Adding Base station and Nodes (2) Direct transmit to base station (3) Out of range node

(4) Skipping low battery node (5) Transmission by shortest path

ResultsSat Sep 19 15:49:03 IST 2015 Consumption (mA): Direct to Base Station:931, Shortest:471Sat Sep 19 15:49:03 IST 2015 Data: {id:7, time: "9/19/15 3:49 PM", Sat Sep 19 15:49:03 IST 2015 Data: {sensor_id: 1, type: "temperature", temperature: "96"},Sat Sep 19 15:49:03 IST 2015 Data: {sensor_id: 2, type: "ecg", status: "normal"},Sat Sep 19 15:49:03 IST 2015 Data: {sensor_id: 3, type: "bp", systolic: 129, diastolic: 83},Sat Sep 19 15:49:03 IST 2015 Data: }Sat Sep 19 15:49:04 IST 2015 Consumption (mA): Direct to Base Station:827, Shortest:827Sat Sep 19 15:49:04 IST 2015 Data: {id:8, time: "9/19/15 3:49 PM", Sat Sep 19 15:49:04 IST 2015 Data: {sensor_id: 1, type: "temperature", temperature: "98"},Sat Sep 19 15:49:04 IST 2015 Data: {sensor_id: 2, type: "ecg", status: "normal"},Sat Sep 19 15:49:04 IST 2015 Data: {sensor_id: 3, type: "bp", systolic: 118, diastolic: 74},Sat Sep 19 15:49:04 IST 2015 Data: }Sat Sep 19 15:49:05 IST 2015 Consumption (mA): Direct to Base Station:1200, Shortest:818Sat Sep 19 15:49:05 IST 2015 Data: {id:9, time: "9/19/15 3:49 PM", Sat Sep 19 15:49:05 IST 2015 Data: {sensor_id: 1, type: "temperature", temperature: "97"},Sat Sep 19 15:49:05 IST 2015 Data: {sensor_id: 2, type: "ecg", status: "normal"},Sat Sep 19 15:49:05 IST 2015 Data: {sensor_id: 3, type: "bp", systolic: 134, diastolic: 75},Sat Sep 19 15:49:05 IST 2015 Data: }Sat Sep 19 15:49:06 IST 2015 Consumption (mA): Direct to Base Station:1045, Shortest:669Sat Sep 19 15:49:06 IST 2015 Data: {id:10, time: "9/19/15 3:49 PM", Sat Sep 19 15:49:06 IST 2015 Data: {sensor_id: 1, type: "temperature", temperature: "97"},Sat Sep 19 15:49:06 IST 2015 Data: {sensor_id: 2, type: "ecg", status: "normal"},Sat Sep 19 15:49:06 IST 2015 Data: {sensor_id: 3, type: "bp", systolic: 126, diastolic: 75},Sat Sep 19 15:49:06 IST 2015 Data: }Sat Sep 19 15:49:07 IST 2015 Consumption (mA): Direct to Base Station:1204, Shortest:608Sat Sep 19 15:49:07 IST 2015 Data: {id:11, time: "9/19/15 3:49 PM", Sat Sep 19 15:49:07 IST 2015 Data: {sensor_id: 1, type: "temperature", temperature: "99"},Sat Sep 19 15:49:07 IST 2015 Data: {sensor_id: 2, type: "ecg", status: "normal"},Sat Sep 19 15:49:07 IST 2015 Data: {sensor_id: 3, type: "bp", systolic: 133, diastolic: 83},Sat Sep 19 15:49:07 IST 2015 Data: }

Log file shows data transmitted and corresponding power required. The highlighted (blue) portion indicates savings because of hopping over other sensor nodes.

Thank you

End of presentation