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Time Bounded Localization in Mobile Wireless Sensor Network

Nasseri, Mona
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1431348082

Abstract Details

2015, Doctor of Philosophy, University of Toledo, College of Engineering.
In a Wireless Sensor Network (WSN), localization in a pre-determined time bound can be a reliable technique to keep communication secured and avoid spoofing. Moreover, for Mobile Wireless Sensor Network (MWSN), where sensors repeatedly move away, estimation of the optimum time to trigger re-localization to calculate the accurate sensor location is essential. However, triggering re-localization at pre-defined time interval without proper consideration of the dynamic movement of sensors is insubstantial and results in a poor resource management. Based on the recently proposed two phase Time Bounded Essential Localization (TBEL) method, where localization is processed in Essential and Global phases, we initially modified it into simpler and more efficient Time Bounded Localization Algorithm (TBL) in which the Essential phase of TBEL is ignored due to the existence of the anchors with known locations mainly for network of static nodes. Towards practical application of the TBL for MWSN, Modified-TBL (MTBL) algorithm is newly proposed in this work, which is efficient to calculate the optimum time to re-trigger the re-localization procedure. The proposed MTBL algorithm calculates the optimum re-triggering time across the entire network and local islands, in two phases; Local and Global Relocalization. In the first phase, clustering method is used to estimate the local re-localization time. Then the evaluated local results are exploited to decide the optimum global re-localization timing in the second phase. For this calculation, multiple patterns of node mobility are investigated and a probabilistic model of the random waypoint (RWP) is selected, and utilized to validate the soundness of the proposed algorithm. Additionally, its accuracy is checked by Cramer Rao Lower Bound (CRLB). By the results of analysis and simulation, a great reduction of location estimation error can be achieved up to 32% for the selected RWP model. To check the aspects of practical implementation, this study also evaluates the performance of TBL on the Cooja simulation platform as it enables not only the simulation of TBL, but the eventual implementation of this algorithm on real world motes. Also the power consumption values for different operation modes are gained that will be used for further investigations. The simulation results show that, in a limited four rounds of communication, 76.67% of nodes would be localized with an average localization error of 0.5 meters in a 200 m × 200 m simulation area including 30 blind nodes and 50 anchors. As the byproduct of the proposed MTBL, an energy and time efficient algorithm is proposed to determine the optimum number of localized nodes that collaborate in the re-localization process using MTBL. In order to perform re-localization, a server node activates the optimal number of localized nodes in each island/cluster. In this regard, a Markov Decision Process (MDP) based algorithm is proposed to find the optimal policy to select those nodes in better condition to cooperate in the re-localization process. The corresponding simulation results show that the proposed MDP algorithm effectively decreases the energy consumption in the WSN between 0.6% and 32%. Furthermore, to decrease the energy consumption and the number of re-transmissions, a Time Bounded Cluster based Localization (TBCL) method is proposed in which localization is performed in distinguishing clusters, and the information is delivered to the Base Station via Clusters Heads. For clustering purpose, a method of Modified-Low Energy Adaptive Clustering Hierarchy (MLEACH) is applied, for power saving and reducing the number of transmissions. In the proposed method, the network is divided into several clusters which are considered as a Local Coordinate systems (LCS) with a Cluster Head (CH) acting as a Relay Node (RN), that encodes and forwards the received packets to the Base Station (BS). Simulation results show the considerable reduction in the number of transmissions and energy consumption comparing with a TBEL case.
Junghwan Kim (Advisor)
Mansoor Alam (Committee Co-Chair)
Robert Green (Committee Member)
Ezzatollah Salari (Committee Member)
Dong-Shik Kim (Committee Member)
116 p.
Electrical Engineering

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Citations

  • Nasseri, M. (2015). Time Bounded Localization in Mobile Wireless Sensor Network [Doctoral dissertation, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1431348082

    APA Style (7th edition)

  • Nasseri, Mona. Time Bounded Localization in Mobile Wireless Sensor Network. 2015. University of Toledo, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1431348082.

    MLA Style (8th edition)

  • Nasseri, Mona. "Time Bounded Localization in Mobile Wireless Sensor Network." Doctoral dissertation, University of Toledo, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1431348082

    Chicago Manual of Style (17th edition)

toledo1431348082
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© 2015, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.