智能配电网无线传感器通信网络的跨层协作控制
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摘要
为提高智能配电网无线传感器网络通信的实时性和可靠性,提出一种堆栈协议层之间跨层协作的控制模型。以无线传感器网络节点内各个影响因素为概念节点,建立起节点内模糊认知图结构模型,利用隶属关系确定该模型内概念节点之间的影响程度,进而建立整个通信系统的跨层控制模型。控制模型根据网络电力数据的通信状态,通过自学习和训练方法获得各个协议层参数之间的影响权重,实时调整物理层、MAC层、传输层参数以及路由策略相互协作,来保证数据通信的实时性和可靠性。最后对系统的网络接收的数据量、节点队列传输数据的平均延时以及网络的吞吐量等指标进行测试。结果表明,所提出的基于模糊认知图的无线传感器网络跨层协作控制方案符合智能配电网无线传感器网络通信特征,并能够满足其通信实时性与可靠性的需求。
In order to improve the real-time and reliability of wireless sensor network communication applied in smart distribution grid,a cross layer collaboration control model for stack protocol layer is proposed. Taken the influencing factors of the wireless sensor communication network as the conception nodes,the in-node fuzzy cognitive map model is established. The subordinative relationship is used to determine the impact between conception nodes,and then the cross layer control model of the whole communication system is established. According to the communication state of the network power data,the influence weights between the parameters of each protocol layer are obtained by self-learning and training methods. The control model adjusts the physical layer,the MAC layer,the transport layer parameters and the routing policy in real-time to ensure real time and reliability of transmission data. Finally,testing experiments for the received data of WSNs network,the average delay of the node queue,and the effective throughput are carried out.Results show that proposed cross layer cooperative control scheme based on fuzzy cognitive map qualifies WSNs communication characteristic of smart distribution grid,and can meet the real-time and reliability requirements.
In order to improve the real-time and reliability of wireless sensor network communication applied in smart distribution grid,a cross layer collaboration control model for stack protocol layer is proposed. Taken the influencing factors of the wireless sensor communication network as the conception nodes,the in-node fuzzy cognitive map model is established. The subordinative relationship is used to determine the impact between conception nodes,and then the cross layer control model of the whole communication system is established. According to the communication state of the network power data,the influence weights between the parameters of each protocol layer are obtained by self-learning and training methods. The control model adjusts the physical layer,the MAC layer,the transport layer parameters and the routing policy in real-time to ensure real time and reliability of transmission data. Finally,testing experiments for the received data of WSNs network,the average delay of the node queue,and the effective throughput are carried out.Results show that proposed cross layer cooperative control scheme based on fuzzy cognitive map qualifies WSNs communication characteristic of smart distribution grid,and can meet the real-time and reliability requirements.
引文
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[17]张玉玲,袁东风,李长春.采用速率兼容LDPC码的AMC-ARQ系统性能分析[J].系统工程与电子技术,2007,29(6):978-981.ZHANG Y L,YUAN D F,LI CH CH.AMC-ARQ system based on RC-LDPC code[J].Systems Engineering and Electronics,2007,29(6):978-981.
[18]赵继军,谷志群,薛亮,等.WSN中层次型拓扑控制与网络资源配置联合设计方法[J].自动化学报,2015,41(3):646-660.ZHAO J J,GU ZH Q,XUE L,et al.A joint design method of hierarchical topology control and network resource allocation for wireless sensor networks[J].Acta Automatica Sinica,2015,41(3):646-660.
[19]LI M,JING Y,LI C.A robust and efficient cross-layer optimal design in wireless sensor networks[J].Wireless Personal Communications,2013,72(4):1889-1902.
[20]王建平,许雨石,孙伟.基于认知图的智能配电网通信性能优化研究[J].电子测量与仪器学报,2015,29(6):816-822.WANG J P,XU Y SH,SUN W.Research of intelligent distribution networks communication based on cognitive maps[J].Journal of Electronic Measurement and Instrumentation,2015,29(6):816-822.
[2]Office of the National Coordinator for Smart Grid Interoperability.NIST framework and roadmap for smart grid interoperability standards:Release 1.0[R].2010.
[3]National Institute of Standards and Technology.Framework and Roadmap for Smart Grid Interoperability Standards Release 2.0[S].2012.
[4]The Institute of Electrical and Electronics Engineers.IEEE Standard for local and metropolitan area net-worksPart 15.4:Low-rate wireless personal area networks(LR-WPANs)amendment 3:Physical layer(PHY)specifications for low-data-rate,wireless,smart metering utility networks[S].2012.
[5]胡智慧,刘智.基于LTE无线传感器在智能电网的应用研究[J]长春理工大学学报(自然科学版),2014,37(2):80-83.HU ZH H,LIU ZH.Research on the application of wireless sensor networks based on LTE in smart grid[J].Journal of Changchun University of Science and Technology(Natural Science Edition),2014,37(2):80-83.
[6]LIN C K,KOKKINOS T.Cross-layer solutions for extended-range wireless sensor networks[J].IEEE Sensors Journal,2013(13):1044-1054.
[7]范兴刚,王恒,蒿翔.有向传感器网络的覆盖增强算法[J].仪器仪表学报,2017,38(2):368-377.FAN X G,WANG H,HAO X.Algorithm for enhancing coverage ratio in directional sensor networks[J].Chinese Journal of Scientific Instrument,2017,38(2):368-377.
[8]DAVID E,XAVIER L,LUIS S.A cross-layer MAC and routing protocol based on slotted aloha for wireless sensor networks[J].Annals of Telecommunications,2015,70(3-4):1-11.
[9]SHI Q,COMANICIU C,WANG D,et al.Cross-layer MAC design for location-aware wireless sensor networks[J].International Journal of Communication Systems,2011,24(7):872-888.
[10]刘雯静,郭静波.基于优先级策略的跨层优化NPLC CSMA/CA机制[J].清华大学学报(自然科学版),2014,54(9):1148-1154.LIU W J,GUO J B.Priority-based cross-layer CSMA/CA for narrowband power line communication[J].Journal of Tsinghua University(Science&Technology),2014,54(9):1148-1154.
[11]张玉鹏,刘凯,王广学.基于无线传感器网络的跨层拥塞控制协议[J].电子学报,2011,39(10):2258-2262.ZHANG Y P,LIU K,WANG G X,et al.Access point selection mechanism based on cross-layer awareness for cognitive networks[J].Journal on Communications,2011,39(10):2258-2262.
[12]赵菁,姚琳.基于综合代价因子的新型卫星网络路由改进算法[J].电子测量技术,2015,38(7):128-134.ZHAO J,YAO L.The improving algorithm of new satellite network route based on integrated consideration of factor[J].Electronic Measurement Technology,2015,38(7):128-134.
[13]周海鸿,周嘉奉.基于Zig Bee技术的温湿度监测系统[J].国外电子测量技术,2015,34(7):75-79.ZHOU H H,ZHOU J F.Temperature and humidity monitoring system based on Zig Bee technology[J].Foreign Electronic Measurement Technology,2015,34(7):75-79.
[14]汪志伟,曹建福,郑辑光.一种面向分簇无线传感器网络的多信道跨层协议[J].西安交通大学学报,2013,47(6):61-67.WANG ZH W,CAO J H,ZHENG J F.Multi-channel multi-path cross-layer protocol for clustered wireless sensor networks[J].Journal of Xian Jiaotong University,2013,47(6):61-67.
[15]欧阳一鸣,陈静雯,梁华国,等.No C中负载均衡的AVOQ路由器设计[J],电子测量与仪器学报,2017,31(1):92-98.OUYANG Y M,CHEN J W,LIANG H G,et al.Design of load-balancing AVOQ router in network-on-chip[J].Journal of Electronic Measurement and Instrumentation,2017,31(1):92-98.
[16]石雷,石怡,魏振春,等.基于干扰管理的无线网络跨层算法研究和设计[J].电子测量与仪器学报,2013,27(11):1005-1010.SHI L,SHI Y,WEI ZH CH,et al.Cross-layer algorithm for the wireless network with interference management[J].Journal of Electronic Measurement and Instrument,2013,27(11):1005-1010.
[17]张玉玲,袁东风,李长春.采用速率兼容LDPC码的AMC-ARQ系统性能分析[J].系统工程与电子技术,2007,29(6):978-981.ZHANG Y L,YUAN D F,LI CH CH.AMC-ARQ system based on RC-LDPC code[J].Systems Engineering and Electronics,2007,29(6):978-981.
[18]赵继军,谷志群,薛亮,等.WSN中层次型拓扑控制与网络资源配置联合设计方法[J].自动化学报,2015,41(3):646-660.ZHAO J J,GU ZH Q,XUE L,et al.A joint design method of hierarchical topology control and network resource allocation for wireless sensor networks[J].Acta Automatica Sinica,2015,41(3):646-660.
[19]LI M,JING Y,LI C.A robust and efficient cross-layer optimal design in wireless sensor networks[J].Wireless Personal Communications,2013,72(4):1889-1902.
[20]王建平,许雨石,孙伟.基于认知图的智能配电网通信性能优化研究[J].电子测量与仪器学报,2015,29(6):816-822.WANG J P,XU Y SH,SUN W.Research of intelligent distribution networks communication based on cognitive maps[J].Journal of Electronic Measurement and Instrumentation,2015,29(6):816-822.