SHU Jian, LIU Song, LIU Linlan, ZHAN Liqin, HU Gang. Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine[J]. Chinese Journal of Electronics, 2017, 26(2): 377-384. doi: 10.1049/cje.2017.01.013
Citation: SHU Jian, LIU Song, LIU Linlan, ZHAN Liqin, HU Gang. Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine[J]. Chinese Journal of Electronics, 2017, 26(2): 377-384. doi: 10.1049/cje.2017.01.013

Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine

doi: 10.1049/cje.2017.01.013
Funds:  This work is supported by the National Natural Science Foundation of China (No.61363015, No.61262020, No.61501218, No.61501217), and the Key Research Foundation of Education Bureau of Jiangxi Province of China (No.GJJ150702).
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  • Corresponding author: LIU Linlan (corresponding author) was born in 1968. She is a professor and M.S. supervisor at the School of Information Engineering in Nanchang Hangkong University. Her main research interests include wireless sensor network and distributed system. (Email:liulinlan@nchu.edu.cn)
  • Received Date: 2014-07-22
  • Rev Recd Date: 2016-07-28
  • Publish Date: 2017-03-10
  • In the application of Wireless sensor networks (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality estimation mechanism is proposed, which is based on Support vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive signal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link quality is divided into five levels according to Packet reception rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial respectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reasonable. Compared with the recent published link quality estimation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.
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  • X.Y. Kui, H.K. Du and J.B. Liang, "An energy-balanced connected dominating sets for data gathering in wireless sensor networks", Acta Electronica Sinica, Vol.41, No.8, pp.1521-1528, 2013. (in Chinese)
    A. Woo, T. Tong, D. Culler, "Taming the underlying challenges of reliable multihop routing in sensor networks", Proc. of International Conference on Embedded Networked Sensor Systems, New York, USA, pp.14-27, 2003.
    Y. Xu and W.C. Lee, "Exploring spatial correlation for link quality estimation in wireless sensor networks", Proc. of IEEE International Conference on Pervasive Computing & Communications (PerCom), Pisa, Italy, pp.200-211, 2006.
    G. Zhou, T. He and S. Krishnamurthy, "Impact of radio irregularity on wireless sensor networks", Proc. of International Conference on Mobile Systems, Boston, Massachusets, USA, pp.125-138, 2004.
    Y.J. Li, Z. Wang and Y.X. Sun, "Analyzing and modeling of the wireless link for sensor networks", Chinese Journal of Sensors and Actuators, Vol.20, No.8, pp.1846-1851, 2007. (in Chinese).
    N. Baccour, A. Koubâa, M.B. Jamâa, et al., "RadiaLE:A framework for designing and assessing link quality estimators in wireless sensor networks", Ad Hoc Networks, Vol.9, No.7, pp.1165-1185, 2011.
    P.G. Sun, H. Zhao, D.D. Luo, et al., "Study on measurement of link communication quality in wireless sensor networks", Communications Journal, Vol.28, No.10, pp.14-22, 2007. (in Chinese)
    N. Reijers, G. Halkes and K. Langendoen, "Link layer measurements in sensor networks", Proc. of IEEE International Conference on Mobile Ad-hoc & Sensor Systems, pp.224-234, 2004.
    J. Zhu, H. Zhao, X.Y. Zhang, et al., "LQI-based evaluation model of wireless link", Journal of Northeastern University (Natural Science), Vol.29, No.9, pp.1262-1265, 2008. (in Chinese)
    M. Senel, K. Chintalapudi, D. Lal, et al., "A Kalman filter based link quality estimation scheme for wireless sensor networks", Proc. of IEEE Global Telecommunications Conference (GLOBECOM), Washington, DC., USA, pp.875-880, 2007.
    L.L. Liu, Y.L. Fan, J. Shu, et al., "A link quality prediction mechanism for wsns based on time series model", Proc. of International Conference on Ubiquitous Intelligence & Computing & International Conference on Autonomic & Trusted Computing, Xi'an, China, pp.175-179, 2010.
    J. Luo, L. Yu, D. Zhang, et al., "A new link quality estimation mechanism based on LQI in WSN", Information Technology Journal, Vol.12, No.8, pp.1626-1631, 2013.
    X.Y. Peng, D.W. Pan, Y. Peng, et al., "On multiple time scales link estimation in wireless sensor network", Acta Electronica Sinica, Vol.39,No.3A, pp.80-85, 2011.(in Chinese)
    Z.Q. Guo, Q. Wang, M.H. Li, et al., "Fuzzy logic based multidimensional link quality estimation for multi-hop wireless sensor networks", IEEE Sensors Journal, Vol.13, No.10, pp.3605-3615, 2013.
    F. Wang, K. He, Y. Liu, et al., "Research on the selection of kernel function in SVM based facial expression recognition", Industrial Electronics and Applications, Vol.34, No.9, pp.789-798, 2013.
    C. Burges, "A tutorial on support vector machines for pattern recognition", Data Mining and Knowledge Discovery, Vol.2, No.2, pp.121-167, 1998.
    M.X. Chu, A.N. Wang and R.F. Gong, "Improvement on least squares twin support vector machine for pattern classification", Acta Electronica Sinica, Vol.42, No.5, pp.998-1003, 2013. (in Chinese)
    C.C. Chang and C.J. Lin, "LIBSVM:A library for support vector machines", ACM Transactions on Intelligent Systems and Technology, Vol.2, No.3, 2011.
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