Real-Time Cyber-Physical Monitoring and Control System Based on Rule Inference
CSTR:
Author:
  • Article
  • | |
  • Metrics
  • |
  • Reference [34]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    Rule-based CPS monitoring methods have significant advantages in reducing monitoring complexity and improving monitoring flexibility. Currently, rule-based CPS monitoring methods do not consider the timing constraints of CPS monitoring scenarios, and only use various optimization techniques to shorten the response time. Based on the real-time rule engine, a real-time monitoring system of CPS, RTCPMS, is established. The system uses Rete network to represent the monitoring rules, and its core is a new real-time inference algorithm Rete-TC. The Rete-TC algorithm introduces the rule deadline, and the timing constraints of CPS monitoring is satisfied as much as possible by the priority-based Beta node scheduling method. The simulation experiment and smart building application case verify the effectiveness of the RTCPMS, and the experimental results show that the core algorithm Rete-TC has a better scheduling success ratio than the traditional rule inference algorithm Rete.

    Reference
    [1] Lee EA. CPS foundations. Design Automation Conference. Anaheim, CA, USA. 2010. 737-742.
    [2] Seshia SA, Hu SY, Li WC, et al. Design automation of cyber-physical systems: Challenges, advances, and opportunities. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2017, 36(9): 1421-1434. [doi: 10.1109/TCAD.2016.2633961
    [3] Kaihara T, Yao Y. A new approach on CPS-based scheduling and WIP control in process industries. Proceedings of the 2012 Winter Simulation Conference. Berlin, Gemany. 2012. 1-11.
    [4] Gong Y, Li SJ. Fusion framework of urban traffic control and route guidance based on cyber-physical system theory. Journal of Highway and Transportation Research and Development (English Edition), 2013, 7(1): 82-89. [doi: 10.1061/JHTRCQ.0000029
    [5] Shi JH, Wan JF, Yan HH, et al. A survey of cyber-physical systems. Proceedings of 2011 International Conference on Wireless Communications and Signal Processing. Nanjing, China. 2011. 1-6.
    [6] Li WJ, Meng WZ, Su CH, et al. Towards false alarm reduction using fuzzy if-then rules for medical cyber physical systems. IEEE Access, 2018, 6: 6530-6539. [doi: 10.1109/ACCESS.2018.2794685
    [7] Hackmann G, Guo WJ, Yan GR, et al. Cyber-physical codesign of distributed structural health monitoring with wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 2014, 25(1): 63-72. [doi: 10.1109/TPDS.2013.30
    [8] 中国电子技术标准化研究院. 信息物理系统白皮书. 2017. 1-110.
    [9] 耿少峰. 面向信息物理系统的主动式复杂事件处理技术研究[博士学位论文]. 长沙: 湖南大学, 2018.
    [10] 李想. 基于主动规则的实时推理技术研究[博士学位论文]. 北京: 中国科学院大学, 2011.
    [11] Sun Y, Wu TY, Zhao GT, et al. Efficient rule engine for smart building systems. IEEE Transactions on Computers, 2015, 64(6): 1658-1669. [doi: 10.1109/TC.2014.2345385
    [12] Sun Y, Wang XK, Luo H, et al. Conflict detection scheme based on formal rule model for smart building systems. IEEE Transactions on Human-Machine Systems, 2015, 45(2): 215-227. [doi: 10.1109/THMS.2014.2364613
    [13] Sun Y, Wu TY, Li XM, et al. A rule verification system for smart buildings. IEEE Transactions on Emerging Topics in Computing, 2017, 5(3): 367-379. [doi: 10.1109/TETC.2016.2531288
    [14] Forgy CL. Rete: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 1982, 19(1): 17-37. [doi: 10.1016/0004-3702(82)90020-0
    [15] Klein R, Xie JQ, Usov A. Complex events and actions to control cyber-physical systems. Proceedings of the 5th ACM International Conference on Distributed Event-Based System. New York, NY, USA. 2011. 29-38.
    [16] Chakravarthy S, Krishnaprasad V, Anwar E, et al. Composite events for active databases: Semantics, contexts and detection. Proceedings of the 20th International Conference on Very Large Data Bases (VLDB). San Francisco, CA, USA. 1994. 606-617.
    [17] Luckham D. The power of events: An introduction to complex event processing in distributed enterprise systems. In: Bassiliades N, Governatori G, Paschke A, eds. Rule Representation, Interchange and Reasoning on the Web. Berlin: Springer, 2008.
    [18] Dean T, Boddy M. An analysis of time-dependent planning. Proceedings of the 7th National Conference on Artificial Intelligence. St. Paul, UK. 1988. 49-54.
    [19] Garvey AJ, Lesser VR. Design-to-time real-time scheduling. IEEE Transactions on Systems, Man, and Cybernetics, 1993, 23(6): 1491-1502. [doi: 10.1109/21.257749
    [20] Lesser VR, Pavlin J. Durfee E. Approximate processing in real-time problem solving. AI Magazine, 1988, 9(1): 49-61. [doi: 10.1609/aimag.v9i1.661
    [21] Mouaddib AI, Charpillet F, Haton JP. GREAT: A model of progressive reasoning for real-time systems. Proceedings of the 6th International Conference on Tools with Artificial Intelligence. New Orleans, LA, USA. 1994. 521-527.
    [22] 李想, 高红菊, 乔颖, 等. 面向物联网的实时复杂事件处理引擎. 小型微型计算机系统, 2015, 36(9): 2047-2053. [doi: 10.3969/j.issn.1000-1220.2015.09.025
    [23] Liu GY, Zhu WD, Saunders C, et al. Real-time complex event processing and analytics for smart grid. Procedia Computer Science, 2015, 61: 113-119. [doi: 10.1016/j.procs.2015.09.169
    [24] Van Woensel W, Abidi SSR. Optimizing semantic reasoning on memory-constrained platforms using the RETE algorithm. In: Gangemi A, Navigli R, Vidal ME, et al., eds. The Semantic Web. Cham: Springer, 2018. 682-696.
    [25] Sottara D, Mello P, Proctor M. A configurable Rete-OO engine for reasoning with different types of imperfect information. IEEE Transactions on Knowledge and Data Engineering, 2010, 22(11): 1535-1548. [doi: 10.1109/tkde.2010.125
    [26] Sottara D, Mello P, Proctor M. Adding uncertainty to a Rete-OO inference engine. In: Bassiliades N, Governatori G, Paschke A, eds. Rule Representation, Interchange and Reasoning on the Web. Berlin: Springer, 2008. 104-118.
    [27] Özacar T, Öztürk Ö, Ünalir MO. Optimizing a rete-based inference engine using a hybrid heuristic and pyramid based indexes on ontological data. JCP, 2007, 2(4): 41-48. [doi: 10.4304/jcp.2.4.41-48
    [28] Xiao D, Zhong XA. Improving rete algorithm to enhance performance of rule engine systems. Proceedings of 2010 International Conference on Computer Design and Applications. Qinhuangdao, China. 2010.
    [29] 孙新, 严西敏, 尚煜茗, 等. 一种基于共享度模型的改进Rete算法. 自动化学报, 2017, 43(9): 1571-1579. [doi: 10.16383/j.aas.2017.c160674
    [30] Ju H, Oh S. Enabling RETE algorithm for RDFS reasoning on apache spark. Proceedings of 2018 IEEE 8th International Symposium on Cloud and Service Computing. Paris, France. 2018. 135-138.
    [31] 汪成亮, 温鑫. 智能环境下分布式Rete算法. 计算机应用, 2016, 36(7): 1893-1898. [doi: 10.11772/j.issn.1001-9081.2016.07.1893
    [32] 规则推理引擎Drools. http://www.drools.org/. [2019-06-13].
    [33] 安捷实时数据库系统Agilor. http://agilor.iscas.ac.cn/. [2019-06-13].
    [34] Albaghdadi M, Briley B, Evens M. Event storm detection and identification in communication systems. Reliability Engineering & System Safety, 2006, 91(5): 602-613. [doi: 10.1016/j.ress.2005.05.001
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

彭程,乔颖,王宏安.基于规则推理的实时信息物理监控系统.计算机系统应用,2020,29(7):70-81

Copy
Share
Article Metrics
  • Abstract:1338
  • PDF: 2484
  • HTML: 1500
  • Cited by: 0
History
  • Received:November 25,2019
  • Revised:December 19,2019
  • Online: July 04,2020
  • Published: July 15,2020
Article QR Code
You are the first991210Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063