Simulation of Sensor Clustering in WBAN Networks Project by: Arundale R. M.Sc. Computer Science Centre for Distance Education Anna University Roll No.: 1314MCS0048 Reg. No.: 75713200003 Guided by: Mr. Kanakasabapathi. V.

Wireless Body Area Networks Introduction 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 CH1 S1.1 S1.2 S1.3 S1.4 CH2 S2.1 S2.2 S2.3 S2.4 CH3 S3.1 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 Administrator Create Base Station and Sensor Clusters, Assign location, Voltage level Start Simulation Load configuration Assign transmission Intervals, Thresholds for Charging and distance Setup Base Station and Sensor node positions View Performance statistics Find shortest Path using Dijkstra's Algorithm Choose first node Simulate Battery discharge Simulate data from node Logs Configuration Find all paths to Base Station Transmit data Choose next

System Block diagram Base Station Sensor Nodes Swing JRE Frontend Simulator JRE Swing Frontend GUI Logs Sensor Nodes Base Station Dijkstra's Shortest path Path finder Config load / save Battery charge / discharge User

Class Diagram

Dijkstra's Algorithm (1) Animation (2) Source: Wikipedia (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

Results Sat Sep 19 15:49:03 IST 2015 Consumption (mA): Direct to Base Station:931, Shortest:471 Sat 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:827 Sat 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:818 Sat 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:669 Sat 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:608 Sat 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