Rimao Huang

Beijing University of Posts and Telecommunications, Beijing, Beijing Shi, China

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Publications (4)2.05 Total impact

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    ABSTRACT: In this paper, we present a distributed fault detection algorithm based on k-means clustering for WSN. The nodes within a cluster are divided into three sub-clustering according to their measurements' similarity. We conclude the sensor nodes' working state from the N recent states of sub-clustering, so as to detect, locate, and get rid of the fault nodes. Simulation results show that the k-means cluster fault detection algorithm has a better performance than the distributed Bayesian algorithms. Moreover, the computational complexity of the proposed algorithm is low.
    Seventh International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2011, Beijing, China, December 16-18, 2011; 01/2011
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    Rimao Huang, Xuesong Qiu, Lanlan Rui
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    ABSTRACT: Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.
    Sensors 01/2011; 11(3):3117-34. · 2.05 Impact Factor
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    ABSTRACT: In WSN, Clustering Routing Algorithm can effectively reduce network energy consumption and prolong network lifetime well. But existed Clustering Routing Algorithms are usually location-based, where data correlations are not considered. There is still data redundancy in the terminal. This paper proposes a data correlation-based virtual clustering approach. It integrates the advantages of clustering technique and data correlation. Nodes that are good data correlated will be partitioned in the same virtual cluster. The experimental results show that the proposed algorithm can reduce the amount of messages sent by the nodes, and reduce the energy consumption. The network lifetime is prolonged as well.
    Seventh International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2011, Beijing, China, December 16-18, 2011; 01/2011
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    ABSTRACT: Coverage control is one of the most important technologies in Wireless Sensor Network (WSN). In the precondition of better coverage quality, how to format optimal coverage with least sensors is a significant problem to be solved. A new incomplete coverage control based on target tracking sensor network which called mobile-constrained optimal target tracking coverage algorithm (MCOTT) is presented. In our approach, static sensors will be pre-deployed, collaborating with mobile sensors to achieve an optimal coverage which based on a target trajectory prediction model. Simulation results show that, MCOTT has more advantages like good robustness, high level of target coverage, low energy consumption. The algorithm can save the number of sensors and prolong the network lifetime effectively.
    Seventh International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2011, Beijing, China, December 16-18, 2011; 01/2011

Publication Stats

2.05 Total Impact Points

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Institutions

  • 2011
    • Beijing University of Posts and Telecommunications
      • State Key Laboratory of Switching and Networking
      Beijing, Beijing Shi, China
    • Fujian Agriculture and Forestry University
      Min-hou, Fujian, China