The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.
References
[1]
Lo, B.; Yang, G. Body Sensor Networks—Research Challenges and Opportunities. Proceedings of the IET Seminar, Antennas Propagation, Body-Centric Wireless Communication, London, UK, 24 April 2007; pp. 26–32.
[2]
Gust, H.B.; Warren, M.S.; Margaret, A.H.; Ian, G.C.; Iain, C.M.; Luc, J.; Dominic, T.; Robert, E.P.; David, J.W.; Derek, T.C.; et al. An Entirely subcutaneous implantable cardioverter-defibrillator. N. Engl. J. Med. 2010, 363, 36–39.
[3]
Chen, M.; Gonzalez, S.; Vasilakos, A.; Cao, H. Body area networks: A survey. Mobile Networks Appl. 2010, 16, 171–193.
[4]
IEEE 802.15.6 TG6. Available online: http://www.ieee802.org/15/pub/TG6.html (accessed on 29 February 2012).
[5]
Davenport, D.M.; Ross, F.J. Wearable and Implantable Body Sensor Networks for Ambulatory Patient Monitoring. The Sixth International Workshop, Berkeley, CA, USA, 10–11 August 2009; pp. 41–45.
[6]
Bohorquez, J.D.; Chandrakasan, A. A 350W CMOS MSK Transmitter and 400W OOK Super-Regenerative Receiver for Medical Implant Communications. IEEE Symposium on VLSI Circuits, Honolulu, HI, USA, 18– 20 June 2008; pp. 32–33.
[7]
Higgins, H. Body Implant Communication—Is it a Reality. Proceedings of Antennas and Propagation for Body-centric Wireless Communication, London, UK, 24 April 2007; pp. 33–36.
[8]
Miller, M.J.; Vaidya, N.H. Minimizing energy consumption in sensor networks using a wakeup radio. Wireless Commun. Network. Conf. 2004, 4, 2335–2340.
[9]
Ameen, M.A.; Ullah, N.; Kwak, K. Design and Analysis of a Mac Protocol for Wireless Body Area Network Using Wakeup-Radio. 11th IEEE International Symposium on Communications and Information Technologies (ISCIT), Hangzhou, China, 12– 14 October 2011. Volume 1; pp. 148–153.
[10]
Shankar, V.; Schwiebert, L. Energy-efficient Protocols for Wireless Communication in Biosensor Networks. 12th IEEE International Symposium, San Diego, CA, USA, 8– 12 January 2001. Volume 1; pp. 114–118.
[11]
Wang, X.; Vasilakos, A.V.; Chen, M.; Liu, Y.; Kwon, T.T. A survey of green mobile networks: Opportunities and challenges. Mobile Networks Appl. 2012, 17, 4–20.
[12]
Chilamkurti, N.; Zeadally, S.; Vasilakos, A.; Sharma, V. Cross-layer support for energy efficient routing in wireless sensor networks. J. Sensors 2009, 2009, 134165, doi:10.1155/2009/134165.
[13]
TinyOS. . Available online: www.tinyos.net/ (accessed on 20 August 2012).
[14]
Shah, B.; James, C.; Hui, D.; Jing, D.; Jeff, R.; Anmol, S.; Brian, S.; Charles, G.; Adam, T.; Richard, H.; et al. MANTIS OS: An embedded multithreaded operating system for wireless micro sensor platforms. ACM Kluwer Mobile Networks Appl. (MONET) 2005, 10, 563–579.
[15]
Kim, K.H.; Kopetz, H. A Real-Time Object Model RTO.k and an Experimental Investigation of Its Potentials. Proceedings of the 18th IEEE Computer Software & Applications Conference, Los Alamitos, CA, USA, 22– 24 September 1994; pp. 392–402.
[16]
Kim, J.G.; Kim, M.H.; Heu, S. Architectures and Functions of the TMO Kernels for Ubiquitous & Embedded Real-Time Distributed Computing. Proceedings of UIC, Wuhan, China, 3–6 September 2006; pp. 71–82.
[17]
Davis, R.; Wellings, A. Dual Priority Scheduling. Proceedings of the 16th IEEE Real-Time Systems Symposium, Pisa, Italy, 4– 7 December 1995; pp. 100–109.
[18]
Moncusi, M.A.; Arenas, A.; Labarta, J. Improving energy saving in hard real time systems via a modified dual priority scheduling. SIGARCH Comput. Archit. 2001, 29, 19–24.
[19]
Kim, H.; Kim, J.G. An Efficient Task Serializer for Hard Real-time TMO Systems. Proceedings of the 11th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing, IEEE Computer Society Press, Orlando, FL, USA; 2008; pp. 405–413.
[20]
Sukor, M.; Ariffin, S. Performance Study of Wireless Body Area Network in Medical Environment. Second Asia International Conference on, Kuala Lumpur, Malaysia, 13–15 May 2008; pp. 202–206.
[21]
Richard, A.; Comroe, D.J.; Costello, Jr. ARQ schemes for data transmission in mobile radio systems. IEEE J. Selective Areas Commun. 1984, 2, 472–481.
[22]
μCOSII. Available online: http://micrium.com/page/home (accessed on 10 July 2010).
[23]
Mainwaring, A.; Polastre, J.; Szewczyk, R.; Culler, D.; Anderson, J. Wireless Sensor Networks for Habitat Monitoring. First ACM International Workshop on Wireless Sensor Networks and Applications, Atlanta, GA, USA, 28 September 2002; pp. 88–97.
