Distributed Sampling, Filtering and Synchronization in Wireless Sensor Networks

  • Author / Creator
    Ahmed, Salman
  • A wireless sensor network (WSN) consists of spatially distributed sensor nodes which are deployed to monitor some process of interest. Although WSNs are very promising, the distributed nature, attributes of wireless networks, and availability of limited resources in WSNs introduce significant theoretical and practical challenges. First, the cooperative control of sensor nodes requires to consider subsystems instead of a single system. Second, the communication capabilities and connectivity of the sensor nodes are limited. Third, the information exchange in the wireless sensor network may be unreliable and suffer transmission delays. Fourth, the availability of limited resources imposes constraints on the sampling rates and time synchronization of sensor nodes. Motivated by these challenges, this thesis studies the design of distributing filtering and sampling techniques in resource constrained WSNs. For distributed filtering, one of the most promising techniques are the linear consensus protocols. A motivating example for studying the application of consensus protocols is to investigate the distributed time synchronization problem in WSNs. In this thesis, we study and propose distributed time synchronization protocols which consider an asynchronous framework where the sensor nodes can have different time-periods, starting times and input update times. The clocks in a WSN are modeled by a time-varying system with time-delay terms. By employing tools from nonnegative matrix and graph theories, the convergence analysis is presented. Most of the standard control and monitoring techniques rely on uniform and synchronized sampling. A sensor node has limited battery resources and their efficient utilization imposes constraints on the time synchronization of the sensor nodes which introduces sampling jitters. In this thesis, we model WSNs employing distributed sampling using filter banks and present the design of synthesis filters to minimize the effects of sampling jitters. We consider two cases for the design of synthesis filters. In the first case, we consider a hybrid filter bank and assume that the sampling jitter is known for each sensor. We employ tools from sampled-data control theory and present a procedure to design optimal H2 synthesis filter bank to handle sampling jitters and reconstruct uniformly sampled measurements. In the second case, we consider a discrete-time filter bank and allow the sampling jitters to be time-varying. Using polytopic matrices to encompass all possible representations of the system matrices, the problem is reduced to an Hinfty optimization problem and the design of pre-processing filters is presented. All the theoretical development and the proposed techniques in this thesis are validated using simulation examples.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Doctor of Philosophy
  • 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.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Electrical and Computer Engineering
  • Specialization
    • Control Systems
  • Supervisor / co-supervisor and their department(s)
    • Chen, Tongwen (Electrical and Computer Engineering)
    • Lynch, Alan (Electrical and Computer Engineering)
    • Zhao, Qing (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Chen, Tongwen (Electrical and Computer Engineering)
    • Zhao, Qing (Electrical and Computer Engineering)
    • Lynch, Alan (Electrical and Computer Engineering)
    • Leung, Henry (Electrical and Computer Engineering, UoC)
    • Qiu, Tony (Civil and Environmental Engineering)