Self-learning and self-adaptive framework for supporting high reliability and low energy expenditure in WSNs

详细信息    查看全文

• 作者：Osama Khader ; Andreas Willig ; Adam Wolisz
• 关键词：Wireless sensor networks ; Periodic traffic ; Self ; learning ; Sensitivity analysis ; Performance analysis
• 刊名：Telecommunication Systems
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：61
• 期：4
• 页码：717-731
• 全文大小：1,219 KB
• 参考文献：1.Glaser, S.D. (2004). Some real-world applications of wireless sensor nodes. In Proceedings of the (SPIE) Symposium on Smart Structures and Materials/ NDE 2004. San Diego, California.
  2.Szewczyk, R., Mainwaring, A., Polastre, J., Anderson, J., & Culler, D. (2004). An analysis of a large scale habitat monitoring application. In Proceedings of the ASM SenSys ’04 (pp. 214–226).
  3.Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., Burgess, S., Dawson, T., Buonadonna, P., Gay, D., & Hong, W. (2005). A macroscope in the redwoods. In Proceedings of the ACM SenSys ’05 (pp. 51–63).
  4.Doherty, L., Lindsay, W., & Simon, J. (2007). Channel-specific wireless sensor network path data. In IEEE 16th Internatioanl Conference on Computer Communications and Networks (ICCCN), 2007 (pp. 89–94). Turtle Bay Resort, Honolulu.
  5.Chen, X., Han, P., He, Q.-S., Tu, S.-L., & Chen, Z.-L. (2006). A multi-channel mac protocol for wireless sensor networks. In Proceedings of the Sixth IEEE International Conference on Computer and Information Technology 2006, CIT ’06 (pp. 224–230). China: Fudan University.
  6.HART Communication Foundation. (2008). TDMA Data Link Layer Specification, HCF SPEC 075 Revision 1.1, 17 May.
  7.ISA. ISA 100: wireless system for automation. Available: http://​isa.​zigbee.​org .
  8.Kim, Y., Shin, H., & Cha, H. (2008). Y-mac: An energy-efficient multi-channel mac protocol for dense wireless sensor networks. In Proceedings of the 7th International Conference on Information Processing in Sensor Networks (IPSN ’08) (pp. 53–63). Washington.
  9.Khader, O., Willig, A., & Wolisz, A. (2009). Distributed wakeup scheduling scheme for supporting periodic traffic in WSNs. In Proceedings of the European Wireless (EW 2009) (pp. 287–292). Aalborg.
  10.Myers, R., & Montgomery, D. (2002). Response surface methodology. New York: Wiley.
  11.Rubinstein, R. Y., & Melamed, B. (1998). Modern simulation and modeling. New York: Wiley.
  12.Khader, O., Willig, A., & Wolisz, A. (2013). An autonomous framework for supporting energy efficiency and communication reliability in WSNs. In Proceedings of the IEEE/IFIP Wireless and Mobile Networking Conference (WMNC’2013). Dubai.
  13.Khader, O., Willig, A., & Wolisz, A. (2011). A simulation model for the performance evaluation of wirelesshart tdma protocol. Technical report, Telecommunication Networks Group, Technical UniversityBerlin, TKN Technical Report Series TKN-11-001, Berlin.
  14.Handziski, V., Koepke, A., Willig, A., & Wolisz, A. (2006). Twist: A scalable and reconfigurable testbed for wireless indoor experiments with sensor network. In Proceedings of the 2nd International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality, (RealMAN 2006) (pp. 63–70). Florence.
  15.Chipcon. (2004). CC2420 2.4 GHz IEEE 802.15.4 / ZigBee-ready RF Transceiver Available: http://​www.​chipcon.​com .
  16.Gay, D., Levis, P., Behren, R.V., Welsh, M., Brewer, E., & Culler, D. (2003). The nesC language: A holistic approach to networked embedded systems. In Proceedings of the ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation (PLDI), San Diego.
  17.Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., & Pister, K. (2000). System architecture directions for networked sensors. ACM SIGPLAN Notices, 35(11), 93–104.CrossRef
  18.Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., & Levis, P. (2009). Collection tree protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys 2009) (pp. 1–13). Berkeley.
  19.Networks, Dust. (2007). Wirelesshart technical data sheet. Dust Networks: White paper.
  20.Varga, A. OMNeT++ discrete event simulation system. Available: http://​www.​omnetpp.​org .
  21.NICTA. The Castalia simulator for Wireless Sensor Networks. Available: http://​castalia.​npc.​nicta.​com.​au
  22.Khader, O., Willig, A., & Wolisz, A. (2012). Analyzing the energy consumption of wirelesshart tdma protocol. Technical report, Telecommunication Networks Group, Technical UniversityBerlin, TKN Technical Report Series TKN-12-00x, Berlin.
  23.Zhang, N., & Anpalagan, A. (2010). Sensitivity of SWAN QoS model in MANETs with proactive and reactive routing: A simulation study. Telecommunications Systems, 44(1–2), 17–27.CrossRef
  24.Dargie, W., Chao, X., & Denko, M. K. (2010). Modelling the energy cost of a fully operational wireless sensor network. Telecommunications Systems, 44(1–2), 3–15.CrossRef
  25.El-Hoiydi, A., Decotignie, J.-D., Enz, C. & Roux, E.L. (2003). Poster abstract: Wisemac, an ultra low power mac protocol for the wisenet wireless sensor network. In Proceedings of the ACM SenSys 03. Los Angeles, California. Poster Abstract.
  26.Hurni, P., Braun, T., & Anwander, M. (2010). Evaluation of WiseMAC and extensions on wireless sensor nodes. Telecommunications Systems, 43(1–2), 49–58.CrossRef
  27.Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (ACM SenSys). Baltimore.
  28.Sthapit, P., & Pyun, J.-Y. (2011). Medium reservation based sensor MAC protocol for low latency and high energy efficiency. Telecommunications Systems, 52(4), 2387–2395.
  29.van, T., & Langendoen, D.K. (2003). An adaptive energy-efficient mac protocol for wireless sensor networks. In Proceedings of the ACM SenSys ’03’. Los Angeles.
  30.Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient mac protocol for wireless sensor networks. In Proceedings of the IEEE INFOCOM 2002. New York.
  31.Khan, B. M., & Ali, F. H. (2013). Collision Free Mobility Adaptive (CFMA) MAC for wireless sensor networks. Telecommunications Systems, 52(4), 2459–2474.CrossRef
  32.Rajendran, V., Obraczka, K., & Garcia-Luna-Aceves, J.J. (2003). Energy-efficient, collision-free medium access control for wireless sensor networks. In Proceedings of the ACM SenSys 03 Los Angeles.
  33.van Hoesel, L., & Havinga, P. (2004). A lightweight medium access protocol for wireless sensor networks. In Proceedings of the INSS, 2004.
  34.HART Communication Foundation. (2008). HART Communication Protocol Specification, HCF SPEC 13 Revision 7.1, 05 June.
  35.Khader, O., & Willig, A. (2013). An energy consumption analysis of the wirelessHART TDMA protocol. Computer Communications, 36(7), 804–816.CrossRef
  
• 作者单位：Osama Khader (1)
  Andreas Willig (2)
  Adam Wolisz (1)
  
  1. Telecommunication Networks Group, Technische Universität Berlin, Berlin, Germany
  2. Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand
  
• 刊物类别：Business and Economics
• 刊物主题：Economics
  Business Information Systems
  Computer Communication Networks
  Artificial Intelligence and Robotics
  Probability Theory and Stochastic Processes
  
• 出版者：Springer Netherlands
• ISSN：1572-9451

文摘

In this paper we proposed, designed and evaluated a novel decentralized and self-learning framework to support both high reliability and energy-efficiency for periodic traffic applications in WSNs. Our autonomous framework comprises three main components: estimation and identification of periodic flows, dynamic wakeup-sleep scheduling and asynchronous channel hopping. With asynchronous channel hopping the frequency hopping pattern is determined by each source node autonomously, and forwarders have to identify and follow the pattern. We also propose a light and efficient controller to eliminate the collision caused by multi-flow overlap at forwarders. We present design and evaluation of our autonomous framework using realistic trace-based simulation. The results show that our asynchronous channel hopping solution improves the packet reception rate compared to the single channel solutions without the need of an expensive signaling and time synchronization overhead. We also show that with this scheme the average energy consumption yields a \(\approx \) 50 % lower than the single channel solutions. Furthermore, we analyze in detail the energy consumption characteristics of our autonomous framework when operated with a popular transceiver, the ChipCon CC2420 and Texas Instruments MSP430 Microcontroller. We analyze how much various factors contribute to the overall energy consumption. These insights provide valuable guidance on where to start with any effort geared towards saving energy.