Leveraging Human Mobility for Communication in Body Area Networks

When a person is walking the RF signal strength of an on-body communication link may exhibit significant fluctuation with peak-to-peak amplitudes beyond 20 dB. Instantaneous signal strength may be noisy, but the smoothed signal typically exhibits a period that matches the person's stride period. We present an opportunistic packet scheduler that extracts a set of Received Signal Strength Indicator (RSSI) samples from application traffic and utilizes an accelerometer to monitor the person's gait cycle. Packets are scheduled based on previous RSSI peaks and the current offset within the gait cycle. We formulate the task of finding a nonoverlapping packet schedule among the different body area network (BAN) devices as a linear programming problem and present an efficient way of solving it with the simplex method. Our experimental evaluation shows that outdoors BAN links with PRR (ratio of correctly received to transmitted packets) values between 50% and 90% can typically be turned into reliable links with PRR values well above 90%. Indoors the improvements are smaller, but still significant at low transmission power. The main price is an increase in packet delivery latency. The energy consumed by the devices is marginal, but the coordinator spends more energy due to signal processing.

[1]  HauerJan-Hinrich Leveraging Human Mobility for Communication in Body Area Networks , 2014 .

[2]  Peter Hall,et al.  Characterization of on-body communication channels , 2002, 2002 3rd International Conference on Microwave and Millimeter Wave Technology, 2002. Proceedings. ICMMT 2002..

[3]  Ramachandran Ramjee,et al.  Bartendr: a practical approach to energy-aware cellular data scheduling , 2010, MobiCom.

[4]  Raffaele D'Errico,et al.  Opportunistic relaying protocols for human monitoring in BAN , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[5]  Mark J. Buller,et al.  Combat medical informatics: present and future , 2002, AMIA.

[6]  A. Hasan,et al.  Organisation for Economic Co-operation and Development , 2007 .

[7]  Guang-Zhong Yang,et al.  Body sensor networks , 2006 .

[8]  Samir Ranjan Das,et al.  A measurement study of interference modeling and scheduling in low-power wireless networks , 2008, SenSys '08.

[9]  Leif Hanlen,et al.  Narrowband channel characterization for Body Area Networks , 2008 .

[10]  Mauro Dell'Amico,et al.  8. Quadratic Assignment Problems: Algorithms , 2009 .

[11]  Eamonn J. Keogh,et al.  Scaling up dynamic time warping for datamining applications , 2000, KDD '00.

[12]  Larbi Talbi,et al.  Human body modelling for prediction of effect of people on indoor propagation channel , 2004 .

[13]  Reinhold Haux,et al.  A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  Xiao Zheng,et al.  Radio Characterization of 802.15.4 and Its Impact on the Design of Mobile Sensor Networks , 2008, EWSN.

[15]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2003, MobiCom '03.

[16]  Vinny Cahill,et al.  802.11 Link Quality and Its Prediction - An Experimental Study , 2004, PWC.

[17]  Eryk Dutkiewicz,et al.  Dynamic power control in Wireless Body Area Networks using reinforcement learning with approximation , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[18]  Vijay Sivaraman,et al.  Adapting radio transmit power in wireless body area sensor networks , 2008, BODYNETS.

[19]  Stefano Tennina,et al.  BANMAC: An Opportunistic MAC Protocol for Reliable Communications in Body Area Networks , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.

[20]  Peter Hall,et al.  Measurements of on-body propagation characteristics , 2002, IEEE Antennas and Propagation Society International Symposium (IEEE Cat. No.02CH37313).

[21]  K. Wac,et al.  Mobile patient monitoring: The MobiHealth system , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[22]  G. Vermeeren,et al.  Path loss model for wireless narrowband communication above flat phantom , 2006 .

[23]  Piet Wambacq,et al.  Indoor body-area channel model for narrowband communications , 2007 .

[24]  Philip Levis,et al.  The β-factor: measuring wireless link burstiness , 2008, SenSys '08.

[25]  Jonathan W. Hui,et al.  T 2 : A Second Generation OS For Embedded Sensor Networks , 2005 .

[26]  S. Drude,et al.  Requirements and Application Scenarios for Body Area Networks , 2007, 2007 16th IST Mobile and Wireless Communications Summit.

[27]  Andreas Terzis,et al.  Design and evaluation of a versatile and efficient receiver-initiated link layer for low-power wireless , 2010, SenSys '10.

[28]  Sirajum Munir,et al.  Addressing burstiness for reliable communication and latency bound generation in wireless sensor networks , 2010, IPSN '10.

[29]  Ingrid Moerman,et al.  A survey on wireless body area networks , 2011, Wirel. Networks.

[30]  Tobias Achterberg,et al.  SCIP: solving constraint integer programs , 2009, Math. Program. Comput..

[31]  Jens Zander,et al.  A body-shadowing model for indoor radio communication environments , 1998 .

[32]  M. Ross,et al.  Average magnitude difference function pitch extractor , 1974 .

[33]  C. Tudor-Locke,et al.  Revisiting "how many steps are enough?". , 2008, Medicine and science in sports and exercise.

[34]  Mauro Dell'Amico,et al.  Assignment Problems , 1998, IFIP Congress: Fundamentals - Foundations of Computer Science.

[35]  Marco Tiloca,et al.  MAC Implementation for TinyOS 2 . 1 , 2011 .

[36]  William Scanlon,et al.  Channel modelling of narrowband body centric wireless communications systems , 2011 .

[37]  Vlado Handziski,et al.  Experimental Study of the Impact of WLAN Interference on IEEE 802.15.4 Body Area Networks , 2009, EWSN.

[38]  Jan-Hinrich Hauer,et al.  Opportunistic Packet Scheduling in Body Area Networks , 2011, EWSN.

[39]  Steffen Leonhardt,et al.  Automatic Step Detection in the Accelerometer Signal , 2007, BSN.

[40]  Paul K. Wright,et al.  A Wireless Sensor Network and Incident Command Interface for Urban Firefighting , 2007, 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous).

[41]  Raffaele D'Errico,et al.  Time-variant BAN channel characterization , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[42]  Vijay Sivaraman,et al.  Algorithms for Transmission Power Control in Biomedical Wireless Sensor Networks , 2008, 2008 IEEE Asia-Pacific Services Computing Conference.

[43]  I. Mr.SHETHMahammedOvesh,et al.  A Survey on Wireless Body Area Network , 2014 .

[44]  David B. Smith,et al.  Transmit power control for wireless body area networks using novel channel prediction , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[45]  Ted K. Ralphs,et al.  Integer and Combinatorial Optimization , 2013 .

[46]  A. Kara,et al.  Blockage/shadowing and polarization measurements at 2.45 GHz for interference evaluation between Bluetooth and IEEE 802.11 WLAN , 2001, IEEE Antennas and Propagation Society International Symposium. 2001 Digest. Held in conjunction with: USNC/URSI National Radio Science Meeting (Cat. No.01CH37229).

[47]  Leif Hanlen,et al.  Body-Area-Network transmission power control using variable adaptive feedback periodicity , 2010, 2010 Australian Communications Theory Workshop (AusCTW).

[48]  P. Levis,et al.  RSSI is Under Appreciated , 2006 .

[49]  Ratko Magjarević Home Care Technologies for Ambient Assisted Living , 2007 .

[50]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[51]  Gaetano Borriello,et al.  Exploiting Mobility for Energy Efficient Data Collection in Wireless Sensor Networks , 2006, Mob. Networks Appl..

[52]  Andreas Komninos,et al.  A pervasive gesture-driven augmented reality prototype using wireless sensor body area networks , 2009, Mobility Conference.

[53]  Andreas Terzis,et al.  Surviving wi-fi interference in low power ZigBee networks , 2010, SenSys '10.

[54]  Nada Golmie,et al.  Prevailing over wires in healthcare environments: benefits and challenges , 2006, IEEE Communications Magazine.

[55]  Nesa L'abbe Wu,et al.  Linear programming and extensions , 1981 .

[56]  George B. Dantzig,et al.  Linear programming and extensions , 1965 .