Research on Network Virtualization Scheme and Networking Algorithm of Advanced Metering Infrastructure for Water, Electricity, Gas, and Heat Meters
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摘要:
为了实现四表(水,电,气,热)集抄行业之间的业务数据隔离,提升本地网络的稳定性和覆盖能力,该文提出四表集抄通信网络虚拟化方案。该方案采用虚拟接入点名称(APN)技术以及软件定义网络(SDN)切片技术构成端到端隔离的业务数据采集通道;采用微功率无线和低压电力线载波构成实时可靠的本地双模虚拟网络,进一步提出基于全局链路状态和分层迭代的组网算法。仿真及现场验证结果表明,该方案降低了采集数据的丢包率和传输时延,提高业务支撑能力,保障行业之间的业务数据隔离,提升通信网络基础设施复用能力。
Abstract:In order to achieve service data isolation in advanced metering Infrastructure for water, electricity, gas, and heat Meters and improve the stability and coverage of local data collection network, a network virtualization scheme of Advanced Metering Infrastructure (AMI) is proposed. In this scheme, the end-to-end isolated service data collection channels are constructed utilizing virtual Access Point Name (APN) and Software Defined Network (SDN) slice technology. The micro-power wireless and low-voltage power line carriers are used to constructed a real-time and reliable local dual mode virtual network. Furthermore, the networking algorithm based on global link-state and hierarchical iterative algorithm are proposed. The simulation and experiments show the packet loss rate and transmission delay of collected data are decreased utilizing the proposed scheme, and business support capability is improved. Moreover, the service data isolation is implemented in AMI for water, electricity, gas, and heat Meters and multiplexing ability of communication network infrastructure is improved.
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表 1 虚拟APN的配置表
业务类型 PGW地址(APN) 主站网关地址(APN) VPN隧道地址(核心网侧) VPN隧道地址(业务主站侧) 业务网络地址池 电力(APN1) 183.230.99.2 183.230.135.2 10.10.10.241/28 10.10.10.242/28 10.0.130.0/24 水务(APN2) 183.230.135.3 10.10.10.243/28 10.10.10.244/28 10.0.131.0/24 燃气(APN3) 183.230.135.4 10.10.10.245/28 10.10.10.246/28 10.0.132.0/24 -
ZHOU Jiazhen, HU Qingyang, and QIAN Yi. Scalable distributed communication architectures to support advanced metering infrastructure in smart grid[J]. IEEE Transactions on Parallel and Distributed Systems, 2012, 23(9): 1632–1642. doi: 10.1109/TPDS.2012.53 胡江溢, 祝恩国, 杜新纲. 用电信息采集系统应用现状及发展趋势[J]. 电力系统自动化, 2014, 38(2): 131–135. doi: 10.7500/AEPS20130617005HU Jiangyi, ZHU Enguo, and DU Xingang. Application status and development trend of power consumption information collection system[J]. Automation of Electric Power Systems, 2014, 38(2): 131–135. doi: 10.7500/AEPS20130617005 华隽. 四表合一采集实现原理及未来发展形势研究[J]. 电力与能源, 2016, 37(4): 445–447. doi: 10.11973/dlyny201604009HUA Juan. " Four-Meter Unified” collection principle and its future development[J]. Power and Energy, 2016, 37(4): 445–447. doi: 10.11973/dlyny201604009 谭周文, 刘宏立, 詹杰, 等. 电力线通信中的基于峰值估计和反馈补偿的自适应噪声抑制[J]. 通信学报, 2017, 38(12): 86–97. doi: 10.11959/j.issn.1000-436x.2017283TAN Zhouwen, LIU Hongli, ZHAN Jie, et al. Adaptive noise mitigation based on peak estimate and feedback compensation in power line communication[J]. Journal on Communications, 2017, 38(12): 86–97. doi: 10.11959/j.issn.1000-436x.2017283 CHEN Xiang, WU Runze, and CAO Min. Research of OFDM power line carrier communication based on AMI[C]. IET International Communication Conference on Wireless Mobile and Computing.Shanghai, China, 2011, 278–281. WANG Hong. A micro-power wireless communication method and device for local detection and control[C]. International Conference on Internet Technology and Applications, Wuhan, China, 2010, 1–3. AMINU B, MURTAL A, and FALAH A. Design and performance analysis of uplinkSchedulers for smart metering over LTE[C]. 2017 IEEE Sensors, Glasgow, UK, 2017: 1–3. 唐伦, 张亚, 梁荣, 等. 基于网络切片的网络效用最大化虚拟资源分配算法[J]. 电子与信息学报, 2017, 39(8): 1812–1818. doi: 10.11999/JEIT161322TANG Lun, ZHANG Ya, LIANG Rong, et al. Virtual resource allocation algorithm for network utility maximization based on network slicing[J]. Journal of Electronics &Information Technology, 2017, 39(8): 1812–1818. doi: 10.11999/JEIT161322 孟洛明, 孙康, 韦磊, 等. 一种面向电力无线专网的虚拟资源优化分配机制[J]. 电子与信息学报, 2017, 39(7): 1711–1718. doi: 10.11999/JEIT161043MENG Luoming, SUN Kang, WEI Lei, et al. Optimal resource allocation mechanism for electric power wireless virtual networks[J]. Journal of Electronics &Information Technology, 2017, 39(7): 1711–1718. doi: 10.11999/JEIT161043 ARUZUAGA A, BERGANZA I, SENDIN A, et al. PRIME interoperability tests and results from field[C]. IEEE International Conference on Smart Grid Communications, Gaithersburg, USA, 2010: 126–130. BAI Leqiang, LIU Yi, QIAN Shiguang, et al. Improved AODVjr routing algorithm based on node depth in ZigBee network[C]. International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, Changsha, China 2016: 2042–2047. 钱志虹, 朱爽, 王雪. 基于分簇机制的Zigbee混合路由能量优化算法[J]. 计算机学报, 2013, 36(3): 485–493. doi: 10.3724/SP.J.1016.2013.00485QIAN Zhihong, ZHU Shuang, and WANG Xue. An cluster-based ZigBee routing algorithm for network energy optimization[J]. Journal of Computer Science, 2013, 36(3): 485–493. doi: 10.3724/SP.J.1016.2013.00485 刘江, 黄韬, 张晨, 等. An cluster-based ZigBee routing algorithm for network energy optimization[J]. 通信学报, 2016, 37(4): 159–171. doi: 10.11959/j.issn.1000-436x.2016083LIU Jiang, HUANG Tao, ZHANG Chen, et al. Research on network virtualization slicing mechanism in SDN-based testbeds[J]. Journal on Communications, 2016, 37(4): 159–171. doi: 10.11959/j.issn.1000-436x.2016083 RAJESH N, XU Ke, WANG K C, et al. An information infrastructure framework for smart grids leveraging SDN and cloud[C]. Clemson University Power Systems Conference(PSC), Clemson, USA, 2016: 1–7. WANG Yamin, LI Xiaoping, and RUIZ R. An exact algorithm for the shortest path problem with position-based learning effects[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(11): 3037–3049. doi: 10.1109/TSMC.2016.2560418 谢志远, 吴晓燕, 杨星, 等. 10kV电力线载波通信自动组网算法[J]. 电力系统自动化, 2012, 36(16): 88–92. doi: 10.3969/j.issn.1000-1026.2012.16.016XIE Zhiyuan, WU Xiaoyan, YANG Xing, et al. Automatically dynamic routing algorithm for 10kV power-line carrier communication[J]. Automation of Electric Power Systems, 2012, 36(16): 88–92. doi: 10.3969/j.issn.1000-1026.2012.16.016