• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Liu Xinhua, Li Fangmin, Kuang Hailan, Fang Yilin. An Distributed and Directed Clustering Algorithm Based on Load Balance for Wireless Sensor Network[J]. Journal of Computer Research and Development, 2009, 46(12): 2044-2052.
Citation: Liu Xinhua, Li Fangmin, Kuang Hailan, Fang Yilin. An Distributed and Directed Clustering Algorithm Based on Load Balance for Wireless Sensor Network[J]. Journal of Computer Research and Development, 2009, 46(12): 2044-2052.

An Distributed and Directed Clustering Algorithm Based on Load Balance for Wireless Sensor Network

More Information
  • Published Date: December 14, 2009
  • Clustering routing protocol for wireless sensor network (WSN) have been growing in recent years. In view of the load balance problem during network clustering for WSN, a distributed and directed clustering algorithm based on load balance is proposed (DDC). In DDC, the pre-evaluation factors which are used for pre-evaluating the energy level and load ability for each node in the next round are presented. During the clustering per round, the whole network is firstly divided into appropriate subareas by the energy pre-evaluation factor, and then the cluster head of each subarea is selected according to the load balance pre-evaluation factor. DDC effectively ensures that the network energy consumption can be decentralized uniformly to every subarea, and that the load for each node in subarea can be balanced. Those characteristics of DDC can organically combine the network energy with the load of node so as to prolong the lifetime of WSN to the greatest extent. The simulation experiments demonstrate that DDC significantly outperforms some similar algorithms such as LEAH and DCHS in terms of energy efficiency, and the load of each node in WSN is more balanced. In the energy-heterogeneous network environments, DDC still has very good adaptability and expandability.
  • Related Articles

    [1]Wu Jinjin, Liu Quan, Chen Song, Yan Yan. Averaged Weighted Double Deep Q-Network[J]. Journal of Computer Research and Development, 2020, 57(3): 576-589. DOI: 10.7544/issn1000-1239.2020.20190159
    [2]Zhu Fei, Wu Wen, Liu Quan, Fu Yuchen. A Deep Q-Network Method Based on Upper Confidence Bound Experience Sampling[J]. Journal of Computer Research and Development, 2018, 55(8): 1694-1705. DOI: 10.7544/issn1000-1239.2018.20180148
    [3]Yang Yatao, Zhang Yaze, Li Zichen, Zhang Fengjuan, Liu Boya. RAKA: New Authenticated Key Agreement Protocol Based on Ring-LWE[J]. Journal of Computer Research and Development, 2017, 54(10): 2187-2192. DOI: 10.7544/issn1000-1239.2017.20170477
    [4]Chen Junyu, Zhou Gang, Nan Yu, Zeng Qi. Semi-Supervised Local Expansion Method for Overlapping Community Detection[J]. Journal of Computer Research and Development, 2016, 53(6): 1376-1388. DOI: 10.7544/issn1000-1239.2016.20148339
    [5]He Xianmang, Chen Yindong, Li Dong, Hao Yanni. Study on Semi-Homogenous Algorithm Based on Ring Generalization[J]. Journal of Computer Research and Development, 2015, 52(10): 2382-2394. DOI: 10.7544/issn1000-1239.2015.20150494
    [6]Yang Shilai, Yang Yahui, Shen Qingni, and Huang Haizhen. A Method of Intrusion Detection Based on Semi-Supervised GHSOM[J]. Journal of Computer Research and Development, 2013, 50(11): 2375-2382.
    [7]Li Yufeng, Huang Shengjun, and Zhou Zhihua. Regularized Semi-Supervised Multi-Label Learning[J]. Journal of Computer Research and Development, 2012, 49(6): 1272-1278.
    [8]Liu Tao, He Yanxiang, Xiong Qi. A Q-Learning Based Real-Time Mitigating Mechanism against LDoS Attack and Its Modeling and Simulation with CPN[J]. Journal of Computer Research and Development, 2011, 48(3): 432-439.
    [9]Chen Shaozhen, Wang Wenqiang, Peng Shujuan. Efficient AttributeBased Ring Signature Schemes[J]. Journal of Computer Research and Development, 2010, 47(12).
    [10]Yang Jian, Wang Jue, Zhong Ning. Laplacian Semi-Supervised Regression on a Manifold[J]. Journal of Computer Research and Development, 2007, 44(7): 1121-1127.

Catalog

    Article views (671) PDF downloads (582) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return