-
摘要: 结合危险品运输监测应用, 搭建了基于无线传感器网络的实时监测系统, 并对其MAC层协议和物理层无线数据发送时序进行了改进和优化。改进了MAC层中的原始BEB算法, 引入了支持优先级的GDCF算法。对MAC层中的RTS/CTS方式进行了有效性分析, 并出于节能考虑, 引入了睡眠技术。在物理层数据无线发送过程中, 为缩短发送时间, 减少碰撞可能性, 对其时序进行了优化。在工程车辆上安装基于IRIS无线传感器的节点平台进行实际测试。测试结果表明: 改进后的退避算法节点丢包率随网络节点数目增加变化不明显; 去除RTS/CTS机制后, 在采样间隔时间为50 ms时, 网络丢包率由20%左右下降到了6%以内; 一个工作周期内节省能量达到95%;无线数据发送时序优化达到了设计要求, 满足了实际应用中对实时监测无线传感网络的性能要求。Abstract: A WSNs-based real-time monitoring system was built in view of the application in hazardous materials transportation monitoring.MAC layer protocol and physical layer transmission time sequence of the monitoring system were improved and optimized.Priority supported GDCF algorithm was introduced after improving the original BEB algorithm of MAC layer.Effectiveness analysis was made for the RTS/CTS mechanism of MAC layer.Sleep mode was introduced for energy saving.Time sequence was optimized to reduce data transmission time and collision probability in physical layer data transmission.Practical test was made by IRIS node platform installing on an engineering automobile.Test result shows that the drop rate using improved backoff algorithm has no significant change with the increase of network node number.The drop rate without RTS/CTS mechanism reduces from the original about 20% to less than 6% when the giving sampling interval time is 50 ms, and 95% energy is saved in every working period.Design goal is achieved in improved time sequence of wireless data transmission, and the performance requirements in real-time monitoring system of WSNs are satisfied in practical application.
-
表 1 采样时间间隔为50 ms时的丢包率
Table 1. Packet loss rates at giving sampling interval time of 50 ms %
分节点 优化前丢包率(有RTS/CTS) 优化后丢包率(无RTS/CTS) 1 23.0 1.2 2 27.0 0.8 3 19.0 6.2 4 26.0 5.1 5 13.0 3.9 6 9.0 1.2 
下载: 导出CSV
表 2 各阶段运行时间
Table 2. Running time of each stage
采样发送时间周期/ms 500 最大时钟漂移Ta/ms 0.63 节点采样发送的实际工作时间Tb/ms 20.98 节点休眠唤醒时间Tc/ms 1.10 节点整体工作时间Ta+Tb+Tc/ms 22.71 节点休眠时间/ms 477.295 节点工作时间占空比/% 4.54
下载: 导出CSV
表 3 优化后的时间测试结果
Table 3. Time test result after optimization
数据有效载荷长度/Byte 4 28 T2-T1/μs 11.9 11.9 T3-T2/μs 27.1 27.1 T4-T3/μs 33.6 105.3
下载: 导出CSV
-
[1] 沈鸿飞, 贾利民. 路网环境下危险品运输的风险控制及应急保障机制研究[J]. 物流技术, 2012, 31(3): 14-16, 43. doi: 10.3969/j.issn.1005-152X.2012.03.004SHEN Hong-fei, JIA Li-min. Emergency support and risk control in hazardous materials transportation within a traffic network[J]. Logistics Technology, 2012, 31(3): 14-16, 43. (in Chinese). doi: 10.3969/j.issn.1005-152X.2012.03.004 [2] 陶存新. 危险品运输预警应急指挥系统研究[D]. 武汉: 武汉理工大学, 2007.TAO Cun-xin. Study on the early warning and emergency command system of dangerous goods transportation[D]. Wuhan: Wuhan University of Technology, 2007. (in Chinese). [3] PLANAS E, PASTOR E, PRESUTTO F, et al. Results of the MITRA project: monitoring and intervention for the transportation of dangerous goods[J]. Journal of Hazardous Materials, 2008, 152(2): 516-526. doi: 10.1016/j.jhazmat.2007.07.032 [4] ZAJICEK J, SCHECHTNER K. Area wide hazardous goods monitoring on the TERN in Austria-project SHAFT[C]∥IEEE. Proceedings of Intelligent Transportation Systems. Vienna: IEEE, 2005: 598-600. [5] 夏涛, 何志标. 危化品运输监控系统的设计与实现[J]. 电子测量技术, 2011, 34(5): 85-89. doi: 10.3969/j.issn.1002-7300.2011.05.024XIA Tao, HE Zhi-biao. Design and implementation of super-visory system for transportation of hazardous chemicals[J]. Electronic Measurement Technology, 2011, 34(5): 85-89. (in Chinese). doi: 10.3969/j.issn.1002-7300.2011.05.024 [6] 姜海亮. 危险品运输车监控系统及其安全性评价[D]. 长春: 吉林大学, 2009.JIANG Hai-liang. Monitoring system and safety evaluation of hazardous chemical tank truck[D]. Changchun: Jilin Univer-sity, 2009. (in Chinese). [7] WARNEKE B, LAST M, LIEBOWITZ B, et al. Smart dust: communicating with a cubic-millimeter computer[J]. IEEE Computer Magzine, 2001, 34(1): 44-51. doi: 10.1109/2.895117 [8] MAINWARING A, POLASTRE J, SZEWCZYK R, et al. Wireless sensor networks for habitat monitoring[C]∥RAGHAVENDRA C S, SIVA-LINGAM K M. Proceedings of the First ACM International Workshop on Wireless Sensor Networks and Applications. Atlanta: ACM Press, 2002: 88-97. [9] SHNAYDER V, CHEN B R, LORINCZ K, et al. Sensor networks for medical care[R]. Boston: Harvard University, 2005. [10] DILMAGHANI R S, BOBARSHAD H, GHAVAMI M, et al. Wireless sensor networks for monitoring physiological signals of multiple patients[J]. IEEE Transactions on Biomedical Cir-cuits and Systems, 2011, 5(4): 347-356. doi: 10.1109/TBCAS.2011.2114661 [11] CARULLO A, CORBELLINI S, PARVIS M, et al. A wire-less sensor network for cold-chain monitoring[J]. IEEE Transactions on Instrumentation and Measurement, 2009, 58(5): 1405-1411. doi: 10.1109/TIM.2008.2009186 [12] RODRIGUEZ-SANCHEZ M C, BORROMEO S, HERNANDEZ-TAMAMES J A. Wireless sensor networks for conservation and monitoring cultural assets[J]. IEEE Sensors Journal, 2011, 11(6): 1382-1389. doi: 10.1109/JSEN.2010.2093882 [13] 惠飞, 赵祥模, 杨飞. 油罐车在途状态监测系统及其任务调度策略[J]. 长安大学学报: 自然科学版, 2011, 31(4): 87-94. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201104018.htmHUI Fei, ZHAO Xiang-mo, YANG Fei. Design of tanker sensor node based WSN and implement of TinyOS tasks scheduling[J]. Journal of Chang'an University: Natural Science Edition, 2011, 31(4): 87-94. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201104018.htm [14] 那成亮. 无线传感器网络MAC层退避算法及功控算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2006.NA Cheng-liang. Research on backoff and power control algorithms for wireless sensor networks MAC layer[D]. Harbin: Harbin Institute of Technology, 2006. (in Chinese). [15] CHATZIMISIOS P, BOUCOUVALAS A C, VITSAS V. Effectiveness of RTS/CTS handshake in IEEE802.11awireless LANs[J]. Electronics Letters, 2004, 40(14): 915-916. https://ieeexplore.ieee.org/document/1315530/ [16] ESTRIN D. Wireless sensor networks tutorial part IV: sensor network protocols[R]. Oakland: University of California, 2002. -
点击查看大图
图(4) / 表(3)
计量
- 文章访问数: 872
- HTML全文浏览量: 145
- PDF下载量: 930
- 被引次数: 0
