Issue 3
Jun.  2017
Turn off MathJax
Article Contents
SU Hang. A Clustering Algorithm of Wireless Sensor Networks for Intelligent Transportation[J]. Journal of Transport Information and Safety, 2017, 35(3): 74-79,106. doi: 10.3963/j.issn.1674-4861.2017.03.010
Citation: SU Hang. A Clustering Algorithm of Wireless Sensor Networks for Intelligent Transportation[J]. Journal of Transport Information and Safety, 2017, 35(3): 74-79,106. doi: 10.3963/j.issn.1674-4861.2017.03.010

A Clustering Algorithm of Wireless Sensor Networks for Intelligent Transportation

doi: 10.3963/j.issn.1674-4861.2017.03.010
  • Publish Date: 2017-06-28
  • Wireless sensor networks (WSNs) are important components of intelligent transportation systems.The energy efficiency of WSNs can benefit from a suitable clustering technique.Based on Energy Efficient Clustering (INEEC) scheme, a clustering algorithm of WSNs is studied in this paper.Operating time is divided into several rounds.Cluster head (CH) is determined in each round to balance energy consumption of CH.During a selection phase of CH, each node chooses a random number and computes the threshold value of the random number by residual energy and the average of the regional energy of all sensors in each cluster.If the random number is less than the threshold value, the node becomes a CH for the current round.Each CH broadcasts a joining request message to the rest of nodes.If a non-CH node receives many joining request messages, the node decides to join the closest cluster accordingly.Those non-CH nodes that do not receive a joining request message are considered as isolated nodes.In order to improve the energy efficiency of an isolated node, INEEC scheme determines its transmission model.Compared with the HEED and LEACH algorithms, the simulation results show that INEEC scheme has better performance in reducing energy consumption which means this scheme has the least isolated nodes, the minimum transmission delay, and a more uniform CH distribution.In detail, the network lifetime increases nearly 23.5% compared with the HEED algorithm.Key problems in the application of the INEEC algorithm, such as high energy consumption, low energy efficiency and network lifetime, are well solved in this study.

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (257) PDF downloads(2) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return