面向多跳无线网络的多干扰源定位算法

doi:10.11959/j.issn.1000-436x.2016284

Abstract

Abstract:

A multiple jammer localization algorithm in multi-hop wireless networks was proposed. The proposed algo-rithm contained three steps, packet delivery ratio (PDR) valley point determination based on gradient descent algorithm, received jamming signal strength (RJSS) peak point determination based on gradient ascent algorithm and cluster analysis. Firstly, the algorithm started from a few initial nodes and moved along the gradient descent direction of PDR to approach the jammers until reaches the PDR valley point. Then, the algorithm moved toward the jammers using power adaptation technique based on RJSS gradient ascent process until it reached the RJSS peak point. Finally, through applying cluster analysis on the neighbour nodes which fail to communicate with RJSS peak points, the number and positions of the jam-mers can be estimated. Experimental results have verified that the proposed algorithm can improve the accuracy of local-ization compared with existed localization algorithms. Furthermore, the performance of the proposed algorithm is promi-nent when the distance of jammers accords with constraint condition.

Key words: multi-hop wireless network, jamming attack, jammer localization, cluster

Qi-ping WANG,Xiang-lin WEI,Jian-hua FAN,Tong-xiang WANG,Fei HU. Multi-hop wireless network oriented multiple jammers localization algorithm[J]. Journal on Communications, 2016, 37(12): 176-186.

Figures/Tables 13

References 25

[1]	XU W , TRAPPE W , ZHANG , et al. The feasibility of launching and detecting jamming attacks in wireless networks[C]// MobiHoc05: Pro-ceedings of the 6th ACM International Symposium on Mobile Ad Hoc networking and Computing. 2005:46-57.
[2]	PELECHRINIS K , KOUFOGIANNAKIS C , KRISHNAMURTHY S . On the efficacy of frequency hopping in coping with jamming attacks in 802.11 networks[J]. IEEE Transactions on Wireless Communica-tions, 2010,9(10):3258-3271.
[3]	NOUBIR G , LIN G . Low-power DoS attacks in data wireless lans and countermeasures[J]. ACM SIGMOBILE Mobile Computing and Comm, 2003,7(3):29-30.
[4]	XU W , TRAPPE W , ZHANG Y . Channel surfing: defending wireless sensor networks from interference[C]// IPSN'07: Proc Sixth Int'l Conf. Information Processing in Sensor Networks. 2007:499-508.
[5]	MA K , ZHANG Y , TRAPPE W . Mobile network management and robust spatial retreats via network dynamics[C]// First Int'l Workshop Resource Provisioning and Management in sensor Networks. 2005:242.
[6]	PELECHRINIS K , KOUFOGIANNAKIS C , KRISHNAMURTHY S . On the efficacy of frequency hopping in coping with jamming attacks in 802.11 networks[J]. IEEE Transactions on Wireless Communica-tions, 2010,9(10):3258-3271.
[7]	NIKA A , ZHANG Z , ZHOU X , et al. Towards commoditized real-time spectrum monitoring[C]// Hotwireless'14. 2014.
[8]	YANG Y , JIN M , WU H . 3D surface localization with terrain model[C]// IEEE Infocom 2014. 2014:46-54.
[9]	孙言强，王晓东，周兴铭．无线网络中的干扰攻击[J]．软件学报， 2012,23(5):1207-1221. SUN Y Q , WANG X D , ZHOU X M . Jamming attacks in wireless network[J]. Journal of Software, 2012,23(5):1207-1221.
[10]	CHENG T Z , LI P , ZHU S C , et al. M-cluster and X-ray: two methods for multi-jammer localization in wireless sensor networks[J]. Inte-grated Computer-Aided Engineering, 2014,21:19-34.
[11]	PELECHRINIS K , KOUTSOPOULOS I , BROUSTIS I , et al. Light-weight jammer localization in wireless networks: system design and implementation[C]// IEEE Global Telecommunication Conference. 2009.
[12]	WANG Q P , WEI X L , FAN J H , et al. A step further of PDR-based jammer localization through dynamic power adaption[C]// WiCOM 2015, 2015:651-654.
[13]	LIU H B , XU W Y , CHEN Y Y , et al. Localizing jammers in wireless networks[C]// PERCOM 2009. Washington: IEEE Computer Society, 2009:1-6.
[14]	LIU Z H , LIU H B , XU W Y , et al. Exploiting jamming-caused neighbor changes for jammer localization[J]. IEEE Trans Parallel Distrib Syst, 2012,23(3):547-555.
[15]	LIU Z H , LIU H B , XU W Y , et al. An error-minimizing framework for localizing jammers in wireless networks[J]. IEEE Trans Parallel Distrib Syst, 2014,25(2):508-517.
[16]	BLUMENTHAL J , GROSSMANN R , GOLATOWSKI F , et al. Weighted centroid localization in Zigbee-based sensor networks[C]// IEEE Int'l Symp on Intelligent Signal Processing Alcala de Henares. 2007:1-6.
[17]	SUN Y Q , WANG X D , ZHOU X M . Geometry-covering based local-ization for jamming attack in wireless sensor networks[J]. Journal on Communications, 2010,31(11):10-16.
[18]	孙言强，王晓东，周兴铭．无线传感器网络中基于几何覆盖的Jamming攻击定位算法[J]．通信学报， 2010,31(11):10-16. SUN Y Q , WANG X D , ZHOU X M . Geometry-covering based local-ization for jamming attack in wireless sensor networks[J]. Journal on Communications, 2010,31(11):10-16.
[19]	CHENG T Z , LI P , ZHU S C . An algorithm for jammer localization in wireless sensor networks[C]// IEEE International Conference on Ad-vanced Information Networking and Applications. 2012:724-731.
[20]	XIONG K Q , DAVID T . Locating jamming attacks in malicious wire-less sensor networks[C]// Performance Computing and Communica-tions Conference(IPCCC), 2012 IEEE 31st international. Austin, TX, 2012:400-407.
[21]	LIU H , LIU Z , CHEN Y , et al. Localizing multiple jamming attackers in wireless networks[C]// 2011 31 International Conference on Distrib-uted Computing Systems. Minneapolis, MN, USA, 2011:517-528.
[22]	VIKRAMADITYA R A , RAGHUVARA R , SHASHIMOHAN V , et al. A novel method for jammer localization in large scale sensor net-works[C]// Wireless And Optical Communications Networks (WOCN), 2010 Seventh International Conference. 2010:6-8.
[23]	KIM Y , MOKAYA F , CHEN E , et al. All your jammers belong to us—localization of wireless sensors under jamming attack[C]// IEEE In-ternational Conference on Communications (ICC). 2012:949-954.
[24]	LIU Z H , LIU H B , XU W Y , et al. Error minimizing jammer localiza-tion through smart estimation of ambient noise[C]// MASS. 2012.
[25]	周世兵，徐振源，唐旭清． K-means算法最佳聚类数确定方法[J]．计算机应用， 2010,30(8):1995-1998. ZHOU S B , XU Z Y , TANG X Q . Method for determining optimal number of clusters in K-means clustering algorithm[J]. Journal of Computer Applications, 2010,30(8):1995-1998.

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参数	含义	默认值
N	网络节点数量	400
M	干扰源数量	3
L	节点部署范围	400m
l	网络栅格长度	20m
PJ	干扰源发射功率	15dBm
PT	节点发射功率	25dBm
O_M/D	干扰源坐标/干扰源间距	(100, 200), (200, 200), (300, 200)/100m
PN	环境噪声功率	?42dBm
IN_MAX	发射功率最大增量	15dBm
SNR_threshold	信噪比阈值	30dB
d_{node_mean}	节点间平均距离	25m
d₀	停止节点与丢失邻居节点平均距离	15m

Multi-hop wireless network oriented multiple jammers localization algorithm

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