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Design and Application of Wireless Machine-to-Machine (M2M) Networks

In the past decades, wireless Machine-to-Machine (M2M) networks have been developed in various industrial and public service areas and envisioned to improve our daily life in next decades, e.g., energy, manufacturing, transportation, healthcare, and safety. With the advantage of low cost, flexible deployment, and wide coverage as compared to wired communications, wireless communications play an essential role in providing information exchange among the distributed devices in wireless M2M networks. However, an intrinsic problem with wireless communications is that the limited radio spectrum resources may result in unsatisfactory performance in the M2M networks. With the number of M2M devices projected to reach 20 to 50 billion by 2020, there is a critical need to solve the problems related to the design and applications in the wireless M2M networks.

In this dissertation work, we study the wireless M2M networks design from three closely related aspects, the wireless M2M communication reliability, efficiency, and Demand Response (DR) control in smart grid, an important M2M application taking the advantage of reliable and efficient wireless communications. First, for the communication reliability issue, multiple factors that affect communication reliability are considered, including the shadowing and fading characteristics of wireless channels, and random network topology. A general framework has been proposed to evaluate the reliability for data exchange in both infrastructure-based single-hop networks and multi-hop mesh networks. Second, for the communication efficiency issue, we study two challenging scenarios in wireless M2M networks: one is a network with a large number of end devices, and the other is a network with long, heterogeneous, and/or varying propagation delays. Media Access Control (MAC) protocols are designed and performance analysis are conducted for both scenarios by considering their unique features. Finally, we study the DR control in smart grid. Using Lyapunov optimization as a tool, we design a novel demand response control strategy considering consumer’s comfort requirements and fluctuations in both the renewable energy supply and customers’ load demands. By considering those unique features of M2M networks in data collection and distribution, the analysis, design and optimize techniques proposed in this dissertation can enable the deployment of wireless M2M networks with a large number of end devices and be essential for future proliferation of wireless M2M networks. / Graduate / 0544 / flintlei@gmail.com

  1. http://hdl.handle.net/1828/5822
  2. Lei Zheng, Simon Parkinson, DanWang, Lin Cai, and Curran Crawford. Energy efficient communication networks design for demand response in smart grid. In proc. IEEE WCSP’11, pages 1–6, November 2011.
  3. Lei Zheng and Lin Cai. Flipped diversity ALOHA in wireless networks with long and varying delay. In proc. IEEE GLOBECOM’11, pages 1–5, December 2011.
  4. Lei Zheng, Ning Lu, and Lin Cai. Reliable wireless communication networks for demand response control. IEEE Transaction on Smart Grid, 4(1):133–140, March 2013.
  5. Lei Zheng, Siyu Lin, and Lin Cai. Efficient multi-receiver message aggregation for short message delivery in M2M networks. In proc. IEEE WCNC’13, pages 274–279, April 2013.
  6. Lei Zheng, Lin Cai, Jianping Pan, and Minming Ni. Performance analysis of grouping strategy for dense IEEE 802.11 networks. In proc. IEEE GLOBECOM’13, pages 1–6, December 2013.
  7. Lei Zheng and Lin Cai. A distributed demand response control strategy using Lyapunov optimization. IEEE Transaction on Smart Grid, 5(4):2075–2083, July 2014.
  8. Lei Zheng, Minming Ni, Lin Cai, Jianping Pan, Chittabrata Ghosh, and Klaus Doppler. Performance analysis of group-synchnized DCF for dense IEEE 802.11 networks. IEEE Transaction Wireless Communications, 13(11):6180–6192, November 2014.
  9. Lei Zheng and Lin Cai. AFDA: Asynchronous flipped diversity ALOHA for emerging wireless networks with long and heterogeneous delay. Accepted by IEEE Transaction on Emerging Topics in Computing, 2014.
Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/5822
Date24 December 2014
CreatorsZheng, Lei
ContributorsCai, Lin
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
RightsAvailable to the World Wide Web, http://creativecommons.org/publicdomain/zero/1.0/

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