B. SC. (HONS) 4TH YEAR PROJECT

Quality of Service Aware MAC Protocol

forBody Sensor Networks

Project Supervisor:Dr. Md. Abdur Razzaque

Associate Professor, Department of Computer Science and engineering,

University of Dhaka.

Presented by:Iffat Anjum (Exam Roll: 543 )Nazia Alam (Exam Roll: 555)

Date: 15th July, 2013

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CONTENTS

Introduction Project Contribution Problem Definition State-of-the-art works Proposed MAC protocol Performance Evaluation

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INTRODUCTION

Body Sensor Network (BSN): wireless network of wearable computing

devices

Applications: Medical and health-care environment Helps to protect those exposed to potentially life threatening environments – e.g., battle field, deep sea divers, space explorers

Entertainment applications

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INTRODUCTION

Figure: General BSN Architecture

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PROJECT CONTRIBUTION Traffic Classification:

Reliability critical packets Delay driven packets Emergency data packets, don’t suffer delay, or

loss.

Priority classification based on: Data generation rate, Traffic class, and Packet size.

Dynamic MAC layer superframe structure

Dynamic inactive period, for sensors and coordinator

Energy Efficiency of the sensor nodes

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PROJECT CONTRIBUTION

We proposed A BSN MAC protocol called PLA-MAC. Performance Evaluated in NS-3 Compared with the State-of-the-art protocols,

IEEE 802.15.4. PNP-MAC.

The proposed protocol has been published in a journal,

International Journal of Distributed Sensor Networks, 2013, as,

Traffic Priority and Load Adaptive MAC Protocol for QoS Provisioning in Body Sensor Networks [32].

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PROBLEM DEFINITION

Giving an alternative solution, Addressing all the short-comings of the state-of-the-art protocols.

Providing a better design and implementation method for BSN.

QoS provisioning (Delay and Reliability): Traffic Classification. Priority Calculation.

Energy efficiency.

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STATE-OF-THE-ART WORK

IEEE 802.15.4 [ 14,15,16] MAC protocol.

Figure: IEEE 802.15.4 Superframe Structure.

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STATE-OF-THE-ART WORK LDTA-MAC [10].

Figure: Superframe structure of LDTA-MAC

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STATE-OF-THE-ART WORK

ATLAS [12].

Figure: Superframe structure of ATLAS

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PNP-MAC[13].

STATE-OF-THE-ART WORK

Figure: Superframe structure of PLA-MAC

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COMPARISON OF THE STATE-OF-THE-ART PROTOCOLS

Table: Characteristics of state-of-the-art protocols

PROPOSED PLA-MAC PROTOCOL

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PROPOSED PLA-MACNetwork Model

Figure: Body sensor network topology

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PROPOSED PLA-MACSuperframe structure

Figure: Proposed PLA-MAC superframe structure

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PROPOSED PLA-MAC

Figure: Overview of the developed QoS architecture

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PROPOSED PLA-MACTraffic Classification

Back-off Calculation

A node that sends either a data packet or a request packet in CAP period , performs a random back-off.

The back-off value is chosen from the range [0, 2Ti+2 -1], Here, Ti is the traffic class number.

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PROPOSED PLA-MAC

The sensor nodes calculates the priority of each packet using the following equation,

Here,

Pi = priority,

Ti = traffic class value,

Gi = data generation rate,

Si = size in bytes.

The packets with the lowest traffic class value (critical packets) and highest data generation rate will have the lowest score and they are defined to have the highest priority.

Priority Calculation

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PROPOSED PLA-MAC

The ETSs are for transmitting emergency data packets that are generated after the CAP period.

Number of ETSs in a superframe is calculated using exponential weighted moving average in the following way:

Here, NumETS = weighted combination of previous value of NumETS

NumEMR = number of emergency packets in the last superframe

Emergency Time Slots (ETS)

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PERFORMANCE EVALUATIONSimulation Environment

Body area sensor network consisting of a single coordinator and a number of sensor devices.

Coordinator uses a single-hop star topology.

Simulation tool: Network Simulator-3.

Compared protocols: IEEE 802.15.4 PNP-MAC

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Network Model

Figure: Body sensor network topology

PERFORMANCE EVALUATION

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PERFORMANCE EVALUATIONSimulation Parameters

Table: Simulation parameters

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PERFORMANCE EVALUATIONPerformance Metrics

Average packet delivery delay

Average delivery delay for delay driven packets

Throughput

Coordinator energy consumption

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Impact of number of nodes

SIMULATION RESULT

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Impact of number of nodes

SIMULATION RESULT

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Impact of number of nodes

SIMULATION RESULT

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Impact of number of nodes

SIMULATION RESULT

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Impact of traffic load

SIMULATION RESULT

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Impact of traffic load

SIMULATION RESULT

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Impact of traffic load

SIMULATION RESULT

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Impact of traffic load

SIMULATION RESULT

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REFERENCES[1] Ameen, M.A.; Nessa, A.; Kwak, K.S. QoS Issues with Focus onWireless Body Area Networks. ICCIT08: Proc. of the 2008 Third Intl Conf. on Convergenceand Hybrid Information Technology; IEEE Computer Society: Washington,USA, 2008; pp. 801807.[2] Latre, B.; Braem, B.; Moerman, I.; Blondia, C. A Survey on Wireless BodyArea Networks. Wireless Networks Volume 17 Issue 1, January 2011.[3] Wood, A.; Stankovic, J.; Virone, G.; Selavo, L.; Zhimin H.; Qiuhua C.; ThaoD.; Yafeng W; Lei F.; Stoleru, R. Context-aware wireless sensor networks forassisted living and residential monitoring. Network, IEEE Volume: 22 Issue 4,July/August 2008.[4] Hanson, M.; Powell, H.; Barth, A.; Ringgenberg, K.; Calhoun, B.; Aylor, J.;Lach, J. Body Area Sensor Networks: Challenges and Opportunities. Computer,IEEE Transactions on 2009, 42, 5865.[5] NIST, http://w3.antd.nist.gov/ban/[6] Fang G.; Dutkiewicz, E. BodyMAC: Energy efficient TDMA-based MAC protocolfor Wireless Body Area Networks. Communications and Information Technology,ISCIT 2009.[7] Marinkovic, S.; Spagnol, C.; Popovici, E. Energy-Efficient TDMA-Based MACProtocol for Wireless Body Area Networks. Third International Conference onSensor Technologies and Applications, 2009.[8] Cavalcanti D.; Schmitt R; Soomro A. Performance Analysis of 802.15.4 and 802.11e for Body Sensor Network Applications. IFMBE Proceedings, 2007, Volume 13, 1st Session, 9-14.

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REFERENCES

[9] Otal B.; Alonso L.; Verikoukis C. Novel QoS scheduling and energy-saving MAC protocol for body sensor networks optimization. BodyNets ’08 Proceedings of the ICST 3rd international conference on Body area networks Article No. 27.

[10] Li, C.; Hao, B.; Zhang, K.; Liu, Y.; Li, J. A novel Medium Access Control protocol with Low Delay and Traffic Adaptivity for wireless body area networks. J. Med. Syst. 2011, 35, 12651275.

[11] Gang Zhou, Jian Lu, Chieh-YihWan, Mark D. Yarvis, and John A. Stankovic, ”BodyQoS-Adaptive and Radio-Agnostic QoS for Body Sensor Networks”, IEEE INFOCOM 2008, April 2008, pp.565-573.

[12] Md. Obaidur Rahman, Choong Seon Hong, Sungwon Lee, and Young-Cheol Bang. ATLAS: A Traffic Load Aware Sensor MAC Design for Collaborative Body Area Sensor Networks”, Sensors 2011, 11, 11560-11580.

[13] June S. Yoon, Gahng-Seop Ahn, Seong-Soon Joo*, Myung J. Lee. PNP-MAC: Preemptive slot allocation and Non-Preemptive transmission for Providing QoS in Body Area Networks, IEEE Communications Society, IEEE CCNC 2010.

[14] IEEE 802.15.4, Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LRWPANs), IEEE, October 1 2003.

[15] Nicholas F. Timmons, William G. Scanlon,“Analysis of the Performance of IEEE 802.15.4 for Medical Sensor Body Area Networking”.

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REFERENCES[16] IEEE 802.15 WPAN Task Group 4 (TG4),

http://www.ieee802.org/15/pub/TG4.html.

[17] Razzaque, M.A.; Hong, C.S.; Lee, S. Data-centric multiobjective QoS-aware routing protocol for body sensor networks. Sensors 2011, 11, 917937.

[18] http://rogers.matse.illinois.edu/research/unusual-format-electronics.php

[19] Benoit Latr , Bart Braem , Ingrid Moerman , Chris Blondia , Piet Demeester, A Survey on Wireless Body Area Networks, WIRELESS NETWORKS, 2011.

[20] S. Park and S. Jayaraman, Enhancing the quality of life through wearable technology, IEEE Engineering in Medicine and Biology Magazine, 2003.

[21] http://www.mediphan.com/distancedoc.php

[22] http://www.globalmed.com/products/telemedicinecarts/transportableexam-stations.php

[23] Sathyanarayana, A.; Nageswaren, S.; Ghasemzadeh, H.; Jafari, R.; Hansen, J.H.L., Body sensor networks for driver distraction identification, Vehicular Electronics and Safety, 2008. ICVES 2008. IEEE, Sept. 2008.

[24] http://www.theparticle.com/cs/bc/net/mac.pdf

[25] Miquel Oliver, Ana Escudero, Study of different CSMA/CA IEEE 802.11- based implementations, EUNICE 1999 Contribution.

[26] David B.Kynor, William E. Audette, Diver Health Monitoring System, Office of Naval Research, Arlington, VA 22203, 2011.

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REFERENCES[27] Dapeng Wu, QoS Provisioning in Wireless Networks, University of Florida,

Prof. Dapeng Wu, University of Florida.

[28] Yanqing Zhang, Yousef Shakhsheer, Adam T. Barth, Harry C. Powell Jr., Samuel A. Ridenour, Mark A. Hanson, John Lach, and Benton H. Calhoun, ‘Energy Efficient Design for Body Sensor Nodes‘, Journal of Low Power Electronics and Applications, 2011.

[29] Buettner, M.; Yee, G.V.; Anderson, E.; Han, R. X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks,SenSys 06, Boulder, CO, USA, 13 November 2006; ACM: Boulder, CO, USA, 2006; pp. 307320.

[30] Ye, W.; Heidemann, J.; Estrin, D. Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 2004, 12, 493506. 13. doi:10.1155/2013/205192.

[31] Sana Ullah, Manar Mohaisen, and Mohammed A. Alnuem, A Review of IEEE 802.15.6 MAC, PHY, and Security Specifications, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 950704, 12 pages, 2013. doi:10.1155/2013/950704.

[32] Iffat Anjum, Nazia Alam, Md. Abdur Razzaque, Mohammad Mehedi Hassan, and Atif Alamri, Traffic Priority and Load Adaptive MAC Protocol for QoS Provisioning in Body Sensor Networks, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 205192, 9 pages, 2013. doi:10.1155/2013/20

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Thank You

Any Question ?