高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于贝叶斯网络的无线传感网高效数据传输方法

刘广怡 李鸥 宋涛 孔范增

刘广怡, 李鸥, 宋涛, 孔范增. 基于贝叶斯网络的无线传感网高效数据传输方法[J]. 电子与信息学报, 2016, 38(6): 1362-1367. doi: 10.11999/JEIT151027
引用本文: 刘广怡, 李鸥, 宋涛, 孔范增. 基于贝叶斯网络的无线传感网高效数据传输方法[J]. 电子与信息学报, 2016, 38(6): 1362-1367. doi: 10.11999/JEIT151027
LIU Guangyi, LI Ou, SONG Tao, KONG Fanzeng. Energy-efficiency Data Transmission Method in WSN Based on Bayesian Network[J]. Journal of Electronics & Information Technology, 2016, 38(6): 1362-1367. doi: 10.11999/JEIT151027
Citation: LIU Guangyi, LI Ou, SONG Tao, KONG Fanzeng. Energy-efficiency Data Transmission Method in WSN Based on Bayesian Network[J]. Journal of Electronics & Information Technology, 2016, 38(6): 1362-1367. doi: 10.11999/JEIT151027

基于贝叶斯网络的无线传感网高效数据传输方法

doi: 10.11999/JEIT151027
基金项目: 

国家科技重大专项(2014ZX03006003)

Energy-efficiency Data Transmission Method in WSN Based on Bayesian Network

Funds: 

The National Science and Technology Major Projects of China (2014ZX03006003)

  • 摘要: 无线环境复杂经常导致高误码率的出现,该文结合无线传感网对传输能耗有较高要求的特点,针对分组协议字段错误修复问题提出基于贝叶斯网络的最大后验修复方法MAP-BN。该方法使得传感网节点在无需任何编码的情况下可以得到向前纠错的能力。MAP-BN算法利用贝叶斯网络对分组协议字段的先验信息进行建模,并在此基础上利用动态规划算法进行最大后验概率推理,成功降低了最大后验修复的计算复杂度。仿真和分析结果表明,MAP-BN算法具有良好的数据差错控制能力,并可以很大程度上提升网络节点传输数据的能效性。
  • ESTRIN D, GOVINDAN R, and HEIDEMANN J. Next century challenges: Scalable coordination in sensor networks[A]. Washington, USA, 1999: 263-270.
    ABOUEI J, EDWARD S, and BROWN J D. On the energy efficiency of LT codes in proactive Wireless Sensor Networks[C]. 2010 25th Biennial Symposium on Communications (QBSC), Kingston, ON. 2010: 114-117.
    郭锐, 刘春于, 张华, 等. 分簇无线传感器网络中根校验全分集LDPC码设计与能效分析[J]. 电子与信息学报, 2015, 37(7): 1580-1585. doi: 10.11999/JEIT141294.
    GUO Rui, LIU Chunyu, ZHANG Hua, et al. Full diversity LDPC codes design and energy efficiency analysis for clustering wireless sensor networks[J]. Journal of Electronics Information Technology, 2015, 37(7): 1580-1585. doi: 10.11999/JEIT141294.
    DELIGIANNIS N, ZIMOS E, OFRIM D M, et al. A distributed joint source-channel coding with copula- function-based correlation modeling for wireless sensors measuring temperature[J]. IEEE Sensors Journal, 2015, 15(8): 4496-4507.
    JING Yue, LIN Zihuai, VUCETIC B, et al. The design of degree distribution for distributed fountain codes in wireless sensor networks[C]. 2014 IEEE International Conference on Communications (ICC), Sydney, 2014: 5796-5801.
    SHIRVANIMOGHDDAM M, LI Yonghui , and VUCETIC B. Sparse event detection in wireless sensor networks using analog fountain codes[C]. 2014 IEEE Global Communications Conference (GLOBECOM), Austin, 2014: 3520-3525.
    ABDERRAZAK A and El FOULY T M. On the distributed binary consensus algorithm in wireless sensor networks[C]. 2013 7th International Conference on Signal Processing and Communication Systems (ICSPCS), Carrara, 2013: 1-9.
    NGUYEN D, LE Quang Vinh Tran, BERDER O, et al. A low-latency and energy-efficient MAC protocol for cooperative wireless sensor networks[C]. 2013 IEEE Global Communications Conference (GLOBECOM), Atlanta, 2013: 3826-3831.
    DUHAMEL P and KIFFER M. Joint Source-channel Decoding: a Cross-layer Perspective with Applications in Video Broadcasting[M]. UK, Academic Press, 2009: 193-246.
    SCHMID F, ORLEAR D, and WEHRLE K. A heuristic header error recovery scheme for RTP[C]. Proceedings of the Wireless On-demand Network Systems and Services (WONS), Alberta, Canada, 2013: 186-190.
    MARIN C, LEPROVOST Y, and KIFFER M. Robust MAC-lite and soft header recovery for packetized multimedia transmission[J]. IEEE Transactions on Communications, 2010, 58(3): 775-782.
    MERIAUX F and KIFFER M. Robust IP and UDP-lite header recovery for packetized multimedia transmission[C]. Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Texas, USA, 2010: 2358-2361.
    王晓梅, 范亮, 陈彦, 等. 一种基于子集约束的协议首部纠错算法[J]. 电子与信息学报, 2015, 37(8): 2014-2020. doi: 10.11999/JEIT141574.
    WANG Xiaomei, FAN Liang, CHEN Yan, et al. Header recovery algorithm based on subset constraint[J]. Journal of Electronics Information Technology, 2015, 37(8): 2014-2020. doi: 10.11999/JEIT141574.
    GAUVAIN J and LEE Chinhui. Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains[J]. IEEE Transactions on Speech and Audio Processing, 1994, 2(2): 291-298.
    BEN MRAD A, DELCROIX V, PIECHOWIAK S, et al. Understanding soft evidence as probabilistic evidence: Illustration with several use cases[C]. 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), Hammamet, 2013: 1-6.
    田真, 袁东风, 梁泉泉. 传感器网络差错控制技术的能效分析[J]. 通信学报, 2008, 29(11): 78-83.
    TIAN Zhen, YUAN Dongfeng, and LIANG Quanquan. Comparison of error control schemes in wireless sensor networks[J]. Journal on Communications, 2008, 29(11): 78-83.
  • 加载中
计量
  • 文章访问数:  1592
  • HTML全文浏览量:  153
  • PDF下载量:  602
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-07-10
  • 修回日期:  2016-02-25
  • 刊出日期:  2016-06-19

目录

    /

    返回文章
    返回