Priority-Based Time-Slot Allocation in Wireless Body Area Networks During Medical Emergency Situations: An Evolutionary Game-Theoretic Perspective

In critical medical emergency situations, wireless body area network (WBAN) equipped health monitoring systems treat data packets with critical information regarding patients' health in the same way as data packets bearing regular healthcare information. This snag results in a higher average waiting time for the local data processing units (LDPUs) transmitting data packets of higher importance. In this paper, we formulate an algorithm for Priority-based Allocation of Time Slots (PATS) that considers a fitness parameter characterizing the criticality of health data that a packet carries, energy consumption rate for a transmitting LDPU, and other crucial LDPU properties. Based on this fitness parameter, we design the constant model hawk-dove game that ensures prioritizing the LDPUs based on crucial properties. In comparison with the existing works on priority-based wireless transmission, we measure and take into consideration the urgency, seriousness, and criticality associated with an LDPU and, thus, allocate transmission time slots proportionately. We show that the number of transmitting LDPUs in medical emergency situations can be reduced by 25.97%, in comparison with the existing time-division-based techniques.

[1]  Vivek Tiwari,et al.  Lacas: learning automata-based congestion avoidance scheme for healthcare wireless sensor networks , 2009, IEEE Journal on Selected Areas in Communications.

[2]  Nadeem Javaid,et al.  Analytical Survey of Wearable Sensors , 2012, 2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications.

[3]  S. K. Panda,et al.  Thermal energy harvesting from human warmth for wireless body area network in medical healthcare system , 2009, 2009 International Conference on Power Electronics and Drive Systems (PEDS).

[4]  Francesco Chiti,et al.  Contention Delay Minimization in Wireless Body Sensor Networks: A Game Theoretic Perspective , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[5]  Sudip Misra,et al.  Using ant-based agents for congestion control in ad-hoc wireless sensor networks , 2009, Cluster Computing.

[6]  B. John Oommen,et al.  Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  H. Balakrishnan,et al.  Mitigating congestion in wireless sensor networks , 2004, SenSys '04.

[8]  Danijela Cabric,et al.  Analysis Framework for Opportunistic Spectrum OFDMA and Its Application to the IEEE 802.22 Standard , 2010, IEEE Transactions on Vehicular Technology.

[9]  Aurel Stefan Gontean,et al.  Packet loss analysis in wireless sensor networks routing protocols , 2012, 2012 35th International Conference on Telecommunications and Signal Processing (TSP).

[10]  A. Sally Hassan,et al.  A survey of Game Theory using Evolutionary Algorithms , 2010, 2010 International Symposium on Information Technology.

[11]  Lin Guan,et al.  A New Congestion Control Mechanism for WSNs , 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

[12]  Shuang-Hua Yang,et al.  Thermal energy harvesting for WSNs , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[13]  S. Vajda,et al.  GAMES AND DECISIONS; INTRODUCTION AND CRITICAL SURVEY. , 1958 .

[14]  Young-mi Baek,et al.  An adaptive rate control for congestion avoidance in wireless body area networks , 2009, 2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.

[15]  Steffen Leonhardt,et al.  Robust Sensor Fusion of Unobtrusively Measured Heart Rate , 2014, IEEE Journal of Biomedical and Health Informatics.

[16]  F. Mtenzi,et al.  Ubiquitous Healthcare Information System: Assessment of its Impacts to Patient’s Information , 2011 .

[17]  Tarik Taleb,et al.  An efficient priority packet scheduling algorithm for Wireless Sensor Network , 2012, 2012 IEEE International Conference on Communications (ICC).

[18]  Georgios Mantas,et al.  A New Framework Architecture for Next Generation e-Health Services , 2013, IEEE Journal of Biomedical and Health Informatics.

[19]  P.E. Ross.  Managing care through the air [remote health monitoring] , 2004, IEEE Spectrum.

[20]  Li-Mei Peng,et al.  An Integrated Healthcare System for Personalized Chronic Disease Care in Home–Hospital Environments , 2012, IEEE Transactions on Information Technology in Biomedicine.

[21]  Carmen C. Y. Poon,et al.  M-Health: The Development of Cuff-less and Wearable Blood Pressure Meters for Use in Body Sensor Networks , 2006, 2006 IEEE/NLM Life Science Systems and Applications Workshop.

[22]  Kunihiro Chihara,et al.  Embedded Ubiquitous Services on Hospital Information Systems , 2012, IEEE Transactions on Information Technology in Biomedicine.

[23]  Victor C. M. Leung,et al.  Enabling technologies for wireless body area networks: A survey and outlook , 2009, IEEE Communications Magazine.

[24]  David Gale,et al.  Review: R. Duncan Luce and Howard Raiffa, Games and decisions: Introduction and critical survey , 1958 .