Presentation on theme: "DAREPage 1 Distance Aware Relaying Energy-efficient: DARE to Monitor Patients in Multi-hop Body Area Sensor Networks Prepared by: Anum Tauqir."— Presentation transcript:
DAREPage 1 Distance Aware Relaying Energy-efficient: DARE to Monitor Patients in Multi-hop Body Area Sensor Networks Prepared by: Anum Tauqir
DAREPage 2 Outline Overview Problem Statement Motivation Brief Overview of M-ATTEMPT and DARE DARE DARE Scenarios Communication Flow Differences and Similarities Simulation Results Conclusion
DAREPage 3 Overview
DAREPage 4 In medical field: WBAN makes use of the tiny sensors for detecting and monitoring different biological characteristics of a human body. The sensors can either be: in-vivo wearable
DAREPage 5 Problem Statement
DAREPage 6 Major concerns for BANs: minimizing energy consumption of the nodes enhancing network lifetime enhancing stability period of the network maximizing throughput minimizing delay
DAREPage 7 Motivation
DAREPage 8 Monitoring different organs of a human body for detecting an ailment or any disorder. The proposed protocol DARE aims: to improve the deficiencies in a BAN protocol of M-ATTEMPT namely, minimum stability period minimum network lifetime high energy consumption low throughput
DAREPage 9 Brief Overview of M-ATTEMPT and DARE
DAREPage 10 M-ATTEMPT a heterogeneous protocol named as, Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop ProTocol DARE a heterogeneous protocol named as, Distance Aware Relaying Energy-efficient Protocol to Monitor Patients in Multi-hop Body Area Sensor Networks
DAREPage 11 DARE
Page 12 Ward dimensions - 40 x 20 ft 2 Five scenarios Eight beds Seven sensors measuring parameters LOS communication Network Topology
DAREPage 13 Classification of Body Sensors
DAREPage 14 Energy Model ParameterValue E TXelec 16.7 nJ/bit E RXelec 36.1 nJ/bit E amp (3.8)1.97 nJ/bit E amp (5.9)7.99 nJ/bit w4000 bits
DAREPage 15 Equations E tx (k,d) = E TXelec * k + E amp (n) * k * d n E rx (k) = E RXelec * k Transmitter Energy Receiver Energy
DAREPage 16 Protocol’s Patient
DAREPage 17 DARE Scenarios
DAREPage 18 Scenario-1 The BSs on each patient carry information and transmit to their respective BR which, then aggregates and relay the received data to the sink located at the center of the ward. The communication flow is from BSs to BR to Sink.
DAREPage 19 Scenario-2 Four sinks have been used that are separately deployed in the middle of the walls of the ward. The BSs of each patient, on sensing the vital sign transmit data to their respective BR. The BR checks for the nearest sink by calculating it’s distance with each sink. Whichever, sink is found nearest, the BR communicates with that particular sink. The communication flow is from BSs to BR to nearest Sink (Sink1 or Sink2 or Sink3 or Sink4).
DAREPage 20 Scenario-3 MS is incorporated on each bed which, can be a PDA type device. The deployment of MS helps the BR to consume little energy as, BR transmits data over shorter distance. However, this scenario increases the delay in the network, as the data traverses through a long route towards the destination node, the Sink. Communication flow is from BSs to BR to MS to Sink.
DAREPage 21 Scenario-4 It follows the same communication flow as sceanrio-1, however, now the sink is made mobile which, moves along the center of ward.
DAREPage 22 Scenario-5 Multiple sinks move around the walls of the ward altogether. In this scenario also, each BR measures it’s distance with each sink. Whosoever is found close, the BR starts communicating with that sink. The communication flow is from BSs to BR to the nearest moving Sink (Sink1 or Sink2 or Sink3 or Sink4).
DAREPage 23 Communication Flow
DAREPage 25 Differences and Similarities DARE M-ATTEMPT
DAREPage 26 ParameterDAREM-ATTEMPT Types of devicesBody Sensors (BSs), Body Relay (BR), Main Sensor (MS), Sink Sensors, Sink DeploymentBSs, BRs and MS are fixed Sink can either be static or mobile Sensors and Sink both are fixed Topology per patient7 BSs 1 BR on chest 7 Sensors 1 Sink on chest Communication flowDepending upon scenarioSensors to Sink or Sensors to other Sensors to Sink Energy parametersE0 BSs = 0.3 J E0 BR = 1 J E MS = infinite E Sink = infinite E0 Sensors = 0.3 J E Sink = infinite Network typeHeterogeneous in terms of energy of BSs and BRs Homogeneous in terms of energy of Sensors Communication typeMulti-hopSingle-hop Multi-hop Types of data reportingEvent-driven Time-driven Event-driven Time-driven
DAREPage 27 Simulation Results
DAREPage 28 Alive Nodes (BSs and Sensors) Number of remaining alive nodes (BSs) in the network
DAREPage 29 Alive Nodes (BSs, BRs and Sensors) Number of remaining alive nodes (BSs + BRs) in the network
DAREPage 30 Residual Energy Residual energy (BSs) of the network
DAREPage 31 Packets Sent to Sink Number of packets sent to sink
DAREPage 32 Throughput (%) Packet delivery ratio
DAREPage 33 Conclusion
DAREPage 34 DARE achieves: increased network lifetime increased stability period From 23% (M-ATTEMPT) to 72% (DARE) minimum energy consumption increased throughput Suitable for networks requiring: no human intervention huge data to transmit However, M-ATTEMPT provides: minimum propagation delay Suitable for networks where: critical data needs to be sent, urgently
DAREPage 35 Comparison results between DARE and M-ATTEMPT ParameterDAREM-ATTEMPT Stability periodhighlow Network lifetimehighlow Energy consumptionminimummaximum Throughputhighlow Propagation delayhighlow