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Extending the Lifetime of Wireless Sensor Networks with Spatial Data Aggregation

  • Author / Creator
    Zou, Shoudong
  • In this thesis, we propose mechanisms to extend the lifetime of wireless sensor networks. In-network data aggregation is considered on both tree-based and flow-based routing protocols during the process of data collection to reduce redundant transmissions. In the flow-based data collection design, we introduce the concept of flow loss multiplier to express the impact of data aggregation over correlated data. The application has the freedom to set the flow loss multiplier to reflect its specific knowledge of correlation. We also introduce traffic balancing as a complementary technique to data aggregation. It helps avoid exhausting the energy of any sensor node while leaving large amounts of energy at other nodes. In tree-based data collection schemes, we adjust the tree structure judiciously to balance energy consumption before any node's failure due to total residual energy depletion. In flow-based schemes, after aggregation, data flows are split and the fragments are spread to increase network lifetime. We investigate the impact of performing greedily data aggregation at the "best" aggregation site regardless of its location, the results of our analysis show that only applying 2-way data aggregation may limit the ability to explore more complex aggregation possibilities. To address this problem, we propose an aggressive data aggregation for a specified application, contour map reconstruction. Based on the simulation results, our aggregation scheme is shown to be able to eliminate large volume of contour data and retain satisfying data accuracy.

  • Subjects / Keywords
  • Graduation date
    2009-11
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3SH39
  • 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
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Nikolaidis, Ioanis (Computing Science)
    • Harms, Janelle (Computing Science)
  • Examining committee members and their departments
    • Sander, Joerg (Computing Science)
    • Kunz, Thomas (Systems and Computer Engineering, Carleton University)
    • Kurgan, Lukasz (Electrical and Computer Engineering)
    • Nascimento, Mario (Computing Science)