Abstract
In this paper, a distributed control scheme of key technologies is designed, which mainly includes QoS (quality of service) identification module and QoS routing optimization module. At the same time, a new routing method is designed to transform routing tables and optimize QoS multicast routing by using quantum evolutionary algorithm. This paper realizes the traditional centralized control of power network, the comprehensive transformation of service and QoS separation mode, and realizes the distributed QoS control mode according to the power service. The experimental results show that the newly designed scheme can provide different QoS guarantees according to different needs of the service and can effectively improve the QoS performance of the power grid.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Binglin, L., Shidong, L., Li, H., Jiming, Y.: Security technology of QoS in power packet transport network. Value Eng. 16, 220–223 (2013)
Dong, F., Han, H., Gong, X., Wang, J., Li, H.: A constellation design methodology based on QoS and user demand in high-altitude platform broadband networks. IEEE Trans. Multimedia 18(12), 2384–2397 (2016)
Dongsheng, Y., Daohao, W., Bowen, Z., Qiyu Chen, Z.Y., Guoyi, X., Mingjian, C.: Key technologies and application prospects of ubiquitous power internet of things. Pow. Gener. Technol. 40(2), 107–114 (2019)
Dou, W., Xu, X., Meng, S., Yu, S.: An Energy-Aware QoS Enhanced Method for Service Computing Across Clouds and Data Centers, pp. 80–87 (2015)
Dou, W., et al.: An energy-aware virtual machine scheduling method for service QoS enhancement in clouds over big data. Concurr. Comput. Pract. Exp. 29(14), e3909 (2017)
Gogoi, S.: A review of the power distribution system in the telecommunications sector. J. Impact Fact. 3, 143 (2018)
Jagatheesan, K., Samanta, S., Choudhury, A., Dey, N., Anand, B., Ashour, A.S.: Quantum inspired evolutionary algorithm in load frequency control of multi-area interconnected thermal power system with non-linearity. In: Hassanien, A.E., Elhoseny, M., Kacprzyk, J. (eds.) Quantum Computing:An Environment for Intelligent Large Scale Real Application. SBD, vol. 33, pp. 389–417. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-63639-9_16
Jordehi, A.R.: Optimisation of demand response in electric power systems, a review. Renew. Sustain. Energy Rev. 103, 308–319 (2019)
Kang-ming, J., Ying, Z., Bo-ren, D., Rui Tang, L.: Risk evaluation method of electric power communication network based on services. Pow. Syst. Protect. Control 41(24), 101–106 (2013)
Li, M., Patiño-Echeverri, D., Zhang, J.J.: Policies to promote energy efficiency and air emissions reductions in china’s electric power generation sector during the 11th and 12th five-year plan periods: Achievements, remaining challenges, and opportunities. Energy Pol. 125, 429–444 (2019)
Luo, J., Ji, P., Wang, X., Zhu, Y.: A Novel Method of QoS Based Resource Management and Trust Based Task Scheduling, pp. 21–32 (2004)
Ning-zhe, X., Hai-feng, Y.: Research on the reliability of electric power telecommunication system. Telecommun. Electr. Pow. Syst. 6, 26–30 (2007)
Qi, L., Chen, Y., Yuan, Y., Fu, S., Zhang, X., Xu, X.: A QoS-aware virtual machine scheduling method for energy conservation in cloud-based cyber-physical systems. In: World Wide Web, pp. 1–23 (2019)
Rao, H., Xu, A., Guo, X., Bai, H., et al.: Strategic research on china energy technology revolution system. Strateg. Study Chin. Acad. Eng. 20(3), 1–8 (2018)
Shuai, S., Zhijun, S., Xiaoguang, Y., Yan, Z., Zhongfeng, W.: A Wireless Extended Coverage Scheme for Electric Power Communication Network, pp. 5836–5840 (2019)
Tingjun, W., Shangdi, M., Xuebing, L., Shanshan, L., Shuo, Z.: Reliability Evaluation Model of Power Communication Network Considering the Importance of Transmission Service, pp. 355–364 (2020)
Villman, G., Lindfors, G., Bergman, S.: Pole for the transmission of electric power and/or telecommunication signals, and use and method (Nov 5 2019), uS Patent 10,465,410
Wei, C., et al.: An optimized service routing allocation method for electric power communication network considering reliability. Pow. Syst. Technol. 37(361)(12), 3541–3545 (2013)
Xin, J., Xiaoyuan, W., Si, L.: Evaluation of communication service importance based on fuzzy analytic hierarchy process. Telecommun. Electr. Pow. Syst. 31(211), 56–61 (2010)
Xue, S., Zhang, Y., Xu, X., Xing, G., Xiang, H., Ji, S.: Qet: a qos-basedenergy-aware task scheduling method in cloud environment. Cluster Comput. 20, 3199–3212 (2017). https://doi.org/10.1007/s10586-017-1047-5
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Jin, S., Liang, X., Tian, H. (2020). QoS Investigation for Power Network with Distributed Control Services. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12486. Springer, Cham. https://doi.org/10.1007/978-3-030-62223-7_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-62223-7_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-62222-0
Online ISBN: 978-3-030-62223-7
eBook Packages: Computer ScienceComputer Science (R0)