[1]金仙力,高军乐,沈一州.基于自适应窗口的盲区数据预警方法[J].南京师范大学学报(工程技术版),2018,18(04):072.[doi:10.3969/j.issn.1672-1292.2018.04.011]
 Jin Xianli,Gao Junle,Shen Yizhou.A Blind Area Data Warning Method Based on Adaptive Window[J].Journal of Nanjing Normal University(Engineering and Technology),2018,18(04):072.[doi:10.3969/j.issn.1672-1292.2018.04.011]
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基于自适应窗口的盲区数据预警方法
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
18卷
期数:
2018年04期
页码:
072
栏目:
计算机工程
出版日期:
2018-12-30

文章信息/Info

Title:
A Blind Area Data Warning Method Based on Adaptive Window
文章编号:
1672-1292(2018)04-0072-08
作者:
金仙力高军乐沈一州
南京邮电大学计算机学院,江苏 南京 210023
Author(s):
Jin XianliGao JunleShen Yizhou
School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
关键词:
自适应窗口盲区预警有限状态机
Keywords:
adaptive windowearly warning in the blind spotfinite state machine
分类号:
TP399
DOI:
10.3969/j.issn.1672-1292.2018.04.011
文献标志码:
A
摘要:
由于障碍物遮挡、设备感应不稳定等因素,区域监控中易产生监控盲区,导致移动媒介存在预警不准确问题. 提出一种自适应窗口的盲区数据预警方法(blind area data warning method,BDWM),该方法根据感知状况、约束关系建立移动区域数据预警模型及预警机制,调整预警阈值,降低盲区的错误预警率,并使用有限状态机推理有效预警状态. 将预警机制应用于RFID数据预警实验,实验结果表明,BDWM可有效降低监控盲区的预警误差率.
Abstract:
A blind zone is easy to occur in regional monitoring due to obstacle obstruction,unstable device induction and other factors,which results in inaccurate warning of mobile media. This paper proposes an adaptive window blind-zone data warning method(BDWM). This method establishes the data warning model of moving zone and the warning mechanism based on the perceived conditions and constraint relationships. It reduces the error rate of the blind zone by adjusting the warning threshold,and reasons the effective warning state using the finite state machine. The warning mechanism is applied to the RFID data warning experiment. The experimental results have shown that BDWM can effectively reduce the error rate of the blind zone.

参考文献/References:

[1] QIAN Z H. Internet of things-oriented wireless sensor networks review[J]. Journal of electronics & information technology,2013,35(1):215-227.
[2]XIE L,YIN Y,VASILAKOS A V,et al. Managing RFID data:challenges,opportunities and solutions[J]. IEEE communications surveys & tutorials,2014,16(3):1294-1311.
[3]AHSAN K,SHAH H,KINGSTON P. RFID applications:an introductory and exploratory study[J]. International journal of computer science issues,2010,7(1):2-4.
[4]QIN Y,SHENG Q Z,FALKNER N J G,et al. When things matter:a survey on data-centric internet of things[J]. Journal of network & computer applications,2016,64:137-153.
[5]谷峪,于戈,张天成. RFID复杂事件处理技术[J]. 计算机科学与探索,2007,1(3):255-267.
GU Y,YU G,ZHANG T C. RFID complex event processing techniques[J]. Journal of computer science and frontiers,2007,1(3):255-267.(in Chinese)
[6]MARCOULLIS I. Self-stabilizing middleware services[C]//The Doctoral Symposium of the International MIDDLEWARE Conference. Trento,Italy:ACM,2016:1-4.
[7]CHU X,ILYAS I F,KRISHNAN S,et al. Data cleaning:overview and emerging challenges[C]//International Conference on Management of Data. San Francisco,USA:ACM,2016.
[8]DARCY P,STANTIC B,SATTAR A. A fusion of data analysis and non-monotonic reasoning to restore missed RFID readings[C]//International Conference on Intelligent Sensors,Sensor Networks and Information Processing. Melbourne,Australia:IEEE,2010.
[9]VALDES A,SKINNER K. Probabilistic alert correlation[C]//Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection. Berlin Heidelberg:Springer-Verlag,2001.
[10]BATENI M,BARAANI A. Time window management for alert correlation using context information and classification[J]. International journal of computer network & information security,2013,5(11):9-16.
[11]JEFFERY S R,GAROFALAKIS M,FRANKLIN M J. Adaptive cleaning for RFID data streams[C]//International Conference on Very Large Data Bases. Seoul,Korea,2006.
[12]MASSAWE L V,VERMAAK H,KINYUA J D M. An adaptive data cleaning scheme for reducing false negative reads in RFID data streams[C]//International Conference on Very Large Data Bases. Seoul,Korea:DBLP,2006.
[13]罗元剑,姜建国,王思叶,等. 基于有限状态机的RFID流数据过滤与清理技术[J]. 软件学报,2014(8):1713-1728.
LUO Y J,JIANG J G,WANG S Y,et al. Filtering and clearing for RFID streaming data technology based on finite state machine[J]. Journal of software,2014(8):1713-1728.(in Chinese)
[14]XIAO Y,JIANG T,LI Y,et al. Data interpolating over RFID data streams for missed readings[M]//Web-Age Information Management. Berlin Heidelberg:Springer,2013:257-265.
[15]晏少华,徐蕾. 基于动态时间阈值的报警聚合方法研究[J]. 沈阳航空航天大学学报,2010,27(5):68-72.
YAN S H,XU L. Alert aggregation method research based on dynamic time threshold[J]. Journal of Shenyang institute of aeronautical engineering,2010,27(5):68-72.(in Chinese)
[16]李伟,门佳. 一种事件驱动有限状态机的编程实现框架[J]. 计算机与现代化,2014(6):116-119.
LI W,MEN J. A programming framework of event-driven finite state machine[J]. Computer and modernization,2014(6):116-119.(in Chinese)

备注/Memo

备注/Memo:
收稿日期:2018-04-18.
基金项目:国家自然科学基金(61472192).
通讯联系人:金仙力,博士,副教授,研究方向:分布式计算、形式化方法等. E-mail:jxl@njupt.edu.cn
更新日期/Last Update: 2018-12-30