Class-based rate differentiation in wireless sensor networks

  • Author / Creator
    Takaffoli, Mansoureh
  • Many applications of wireless sensor networks (WSNs) require the sensor nodes of a network to belong to different priority classes where the nodes of a higher priority class enjoy higher data rates than nodes of a lower priority class.
    Practical design of such networks, however, faces challenges in satisfying the following basic design requirements:
    a) the need to rely on the medium access control mechanisms provided by the IEEE 802.15.4 standard for low-rate wireless personal area networks,
    b) the need to solve certain types of class size optimization problems to ensure adequate sensing coverage, and
    c) the need to achieve good utilization of the available channels.

    Unfortunately, the current version of the IEEE 802.15.4 does not provide adequate support for rate differentiation. Hence, many proposed solutions to the problem in the literature consider adding extensions to the standard.

    In this thesis, we introduce some class size optimization problems as examples of coverage problems that may arise in designing a WSN. We then consider a method proposed in the literature for handling the rate differentiation problem.
    The method relies on modifying the CSMA-CA channel access mechanism of the IEEE standard.
    We use simulation to examine its performance and its applicability to solve some class size optimization problems.
    We next investigate the use of Time Division Multiple Access (TDMA) protocols in providing service differentiation among different classes of sensors.
    We show simple sufficient conditions for the existence of TDMA-based solutions to a class size feasibility problem.

    Lastly, we consider the use of Guaranteed Time Slots (GTS) of the IEEE 802.15.4 standard in constructing TDMA schedules.
    We present a new algorithm that uses the GTS service to construct such schedules. The desired algorithm contains some optimization features.
    The obtained simulation results show the performance gain achieved by the algorithm.

  • Subjects / Keywords
  • Graduation date
    Fall 2009
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.