Xiaolei Guo

Beijing University of Aeronautics and Astronautics (Beihang University), Peping, Beijing, China

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Publications (5)2.97 Total impact

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    ABSTRACT: Multihop localization is a popular approach for determining the positions of normal nodes in large-scale wireless sensor networks. However, most existing multihop localization studies assume that the declared positions of beacon nodes are always reliable or even free of errors, which is not a valid assumption in practice. In this paper, we propose a robust multihop localization algorithm (RMLA) based on trust evaluation for diminishing the effect of unreliable beacons on the accuracy of node localization. Firstly, the trust evaluation framework is established on the basis of evidence theory. According to the multihop geometric relationship among nodes, every beacon evaluates the reliability of other beacons' declared positions. Then, the normal nodes integrate the evaluation results to obtain the total trust degrees of their multihop communication beacons, by use of an average method or an enhanced D-S evidence combination rule. Finally, the normal nodes employ the weighted Taylor-series least squares solver to estimate the optimal values of their coordinates. Extensive simulation results in isotropic and anisotropic networks show the robustness and effectiveness of our algorithm.
    International Journal of Distributed Sensor Networks 01/2012; 2012. · 0.92 Impact Factor
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    ABSTRACT: As a distributed underwater network with wireless sensors, Underwater Wireless Sensor Networks (UWSNs) can provide the means for real-time, accurate and extensive monitoring, it is considered as an ideal system for extensive aqueous environment surveillance. Although localization has been widely studied for terrestrial WSNs, the adverse aqueous environments and harsh acoustic communications all bring new challenges for UWSNs and make it necessary to develop new localization schemes. In this paper, we propose a novel cube-scan-based three dimensional (3D) multi-hop localization algorithm for large-scale UWSNs. Firstly, based on the geometric constraint relationship and the depth information of sensor nodes, we effectively restrict the scope of the to-be-localized node position by a feasible set. Then we study the factors that influence the multi-hop distance estimation, a weighted constrained multi-hop localization model has been constructed. Finally, the feasible set is divided into some sub-cubes of equal size, the approximately optimal values of nodes' coordinates can be obtained through a cube-scanning procedure. Simulation results show that our scheme can achieve high localization accuracy with low communication overhead in large-scale UWSNs.
    01/2012;
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    ABSTRACT: For large-scale wireless sensor networks (WSNs) with a minority of anchor nodes, multi-hop localization is a popular scheme for determining the geographical positions of the normal nodes. However, in practice existing multi-hop localization methods suffer from various kinds of problems, such as poor adaptability to irregular topology, high computational complexity, low positioning accuracy, etc. To address these issues in this paper, we propose a novel Multi-hop Localization algorithm based on Grid-Scanning (MLGS). First, the factors that influence the multi-hop distance estimation are studied and a more realistic multi-hop localization model is constructed. Then, the feasible regions of the normal nodes are determined according to the intersection of bounding square rings. Finally, a verifiably good approximation scheme based on grid-scanning is developed to estimate the coordinates of the normal nodes. Additionally, the positioning accuracy of the normal nodes can be improved through neighbors' collaboration. Extensive simulations are performed in isotropic and anisotropic networks. The comparisons with some typical algorithms of node localization confirm the effectiveness and efficiency of our algorithm.
    Sensors 01/2011; 11(4):3908-38. · 2.05 Impact Factor
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    ABSTRACT: Due to single reference information priority, poor network topology adaptability, low positioning accuracy and high computational complexity, the multi-hop localization approaches for wireless sensor networks have many limitations in application. In view of this, a novel grid-scan-based multi-hop localization algorithm (GSML) is proposed. We construct a more realistic weighted constrained model for multi-hop localization and give the rule of weight assignment. Based on the intersections of bounding square rings, the normal nodes can estimate their feasible regions as small as possible with only a few floating-point operations. On that basis, the approximately optimal values of normal nodes' coordinates can be obtained through a lightweight grid-scan procedure and further improved by the collaboration between neighboring nodes. Extensive simulations show that GSML outperforms the existing typical schemes in aspects mentioned above.
    01/2010;
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    ABSTRACT: Lifetime network is the main considering problem when deploying wireless sensor networks for integrity monitoring of pipeline infrastructures. And the low network lifetime is always caused by the unbalanced energy consumption in the monitoring networks. So in this paper, a sort of data transmission approach based on probabilistic model is put forward to solve the energy consumption unbalanced and enhance the network lifetime. The optimal problem for maximum network lifetime is introduced, which is solved by artificial fish school algorithm. A series of simulation experiments are carried out to verify the effectiveness of new method. Compared with Direct and Multi-hop methods, new method not only can efficiently balance the network energy load, but also can significantly prolong the network lifetime, meeting the requirements of real-time pipeline monitoring.
    Procedia Engineering. 24:64–68.

Publication Stats

2 Citations
2.97 Total Impact Points

Institutions

  • 2012
    • Beijing University of Aeronautics and Astronautics (Beihang University)
      • School of Instrumentation Science and Opto-electronics Engineering (SISOE)
      Peping, Beijing, China