[1]伍转华,潘 立,王永利.传感数据世系的有效压缩传输与查询方法[J].南京理工大学学报(自然科学版),2017,41(01):47.[doi:10.14177/j.cnki.32-1397n.2017.41.01.007]
　Wu Zhuanhua,Pan Li,Wang Yongli.Efficient compression propagating and querying method forsensor data lineage[J].Journal of Nanjing University of Science and Technology,2017,41(01):47.[doi:10.14177/j.cnki.32-1397n.2017.41.01.007]
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传感数据世系的有效压缩传输与查询方法()
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《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年01期
页码:
47
栏目:
出版日期:
2017-02-28

文章信息/Info

Title:
Efficient compression propagating and querying method forsensor data lineage
文章编号:
1005-9830(2017)01-0047-12
作者:
伍转华1; 潘 立2; 3; 王永利3
1.常州纺织服装职业技术学院 机电工程系,江苏 常州 213164; 2.中国人民解放军火箭军参谋部,中国 北京 100085; 3.南京理工大学 计算机科学与工程学院,江苏 南京 210094
Author(s):
Wu Zhuanhua1; Pan Li2; 3; Wang Yongli3
1.Department of Electromechanical Engineering,Changzhou Textile Garment Institute,Changzhou 213164,China; 2.Staff of PLA Rocket Force,Beijing 100085,China; 3.School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
关键词:
传感数据世系;  压缩感知;  列存储;  时空相关;  近似查询
Keywords:
sensor data lineage;  compressed sensing;  column storage;  temporal and spatial correlation;  approximate query
分类号:
TP311
DOI:
10.14177/j.cnki.32-1397n.2017.41.01.007
摘要:
为了有效地分析传感器网络应用中产生数据异常的原因并形成追溯链,该文提出一种基于感知压缩和列存储理论的传感数据世系压缩传输、存储与查询(Compressed propagating storing and querying of sensor data lineage,CPSQSDL)方法。论文分析被感知事件的传感数据世系之间蕴含有时间、空间相关关系,设计了一种适合传感数据世系压缩感知的随机投影观测矩阵,保证CPSQSDL方法具有近似k-term的最优恢复误差。论文对压缩世系进行了形式化定义,给出了近似世系查询算法,形式化证明了压缩世系的恢复误差边界,并在真实数据集上通过实验验证了此方法的有效性。
Abstract:
In order to analyze the reason that generates the abnormal data in sensor network applications effectively and to construct the tracing chain,we propose a transmission and storage method based on compressed sensing and column stored theory for the sensor data lineage,called CPSQSDL(Compressed propagating,storing and querying of sensor data lineage),in this paper.We analyze the temporal and spatial correlation among the sensor data lineages of events,and find a suitable randomized projection observation matrix to ensure that k-term optimal reconstruction error.We describe the formal definition of compressed sensor lineage and design an algorithm for querying approximate lineage and formal proof of its error boundary.Experiments on the real data set prove the effectiveness of the proposed method.

参考文献/References:

[1] Reddy S,Chen Gong,Fulkerson B,et al.Sensor-internet share and search-enabling collaboration of citizen scientists[C]//Proceedings of the ACM Workshop on Data Sharing and Interoperability on the World-wide Sensor Web.Cambridge,Mass.,USA:ACM Press,2007:11-16.
[2]Dogan S G.ProTru:a provenance-based trust architecture for wireless sensor networks[J].International Journal of Network Management,2016,26(2):131-151.
[3]Wang J,Crawl D,Purawat S,et al.Big data provenance:Challenges,state of the art and opportunities[C]// IEEE International Conference on Big Data.Santa Clara,CA,USA:IEEE Press,2015:2509-2516.
[4]Dogan G.A survey of provenance in wireless sensor networks[J].Adhoc & Sensor Wireless Networks,2016,30(1/2):21-35.
[5]Gammack D,Scott S,Chapman A P.Modelling provenance collection points and their impact on provenance graphs[C]//Provenance and Annotation of Data and Processes.New York,USA:Springer International Publishing,2016.
[6]Christopher Ré,Dan Suciu.Approximate lineage for probabilistic databases[C]//Proceeding of the 31th International Conferance on Very Large Data Base(VLDB’08).Auckland,New Zealand:VLDB Press,2008:797-808.
[7]Kanagal B,Deshpande A.Lineage processing over correlated probabilistic databases[C]//SIGMOD’10.Indianapolis,Indiana,USA:ACM Press,2010:675-686.
[8]Razzaque M A,Dobson S.Energy-efficient sensing in wireless sensor networks using compressed sensing[J].Sensors,2014,14(2):2822-2859.
[9]Donoho D L.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[10]Park U,Heidemann J.Provenance in sensor net republishing[C]//Proceeding of the 2nd International Provenance and Annotation Workshop.Salt Lake City,UT,USA:Springer Press,2008:280-292.
[11]Blount M,Davis J,Misra A,et al.A time-and-value centric provenance model and architecture for medical event streams[C]//Proceedings of the 1st International Workshop on Systems and Networking Support for Healthcare and Assisted Living Environments.San Juan,Puerto Rico,USA:Acm Sigmobile Society,2007:95-100.
[12]Misra A,Blount M,Kementsietsidis A,et al.Advances and challenges for scalable provenance in stream processing system[C]//Proceeding of the 2nd International Provenance and Annotation Workshop.Salt Lake City,UT,USA,2008:253-265.
[13]Halaschek-Wiener C,Golbeck J,Schain A,et al.Annotation and provenance tracking in semantic web photo libraries[C]//Proceedings of the 1st International Provenance and Annotation Workshop.Chicago,Illinois,USA:Springer Press,2006:82-89.
[14]Benjelloun A,Das Sarma A,Halevy J,et al.ULDBs:Databases with uncertainty and lineage[C]//Proceedings of the 32nd International Conference on Very Large Data Bases.Seoul,Korea:VLDB Press,2006:953-964.
[15]OPM:twiki,Open Provenance Model Wiki[EB/OL].URL http://twiki.ipaw.info/bin/view/OPM/,2009.
[16]Candes E,Tao T.Near optimal signal recovery from random projections:Universal encoding strategies[J].IEEE Transactions on Information Theory,2006,52(12):5406-5425.
[17]Donoho D.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[18]Achlioptas D.Database-friendly random projections:Johnson-Lindenstrauss with binary coins[J].Journal of Computer and System Sciences,2003:66(4):671-687.
[19]Tropp J A,Gilbert A C.Signal recovery from partial information by orthogonal matching pursuit[EB/OL].April 2005,www.personal.umich.edu/-jtropp/papers/ TG05-Signal-Recovery.pdf.
[20]The Gene Ontology Consortium.Gene ontology:tool for the unification of biology[J].Nature Genet,2000,25(1):25-29.

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备注/Memo

备注/Memo:
收稿日期:2016-05-27 修回日期:2016-10-03
基金项目:国家自然科学基金(61170035; 61272420); 江苏省“六大人才高峰”高层次人才项目(WLW-004); 中央高校基本科研业务费专项资金项目(30916011328); 江苏省科技成果转化专项资金项目(BA2013047)
作者简介:伍转华(1978-),男,讲师,主要研究方向:数据库技术、无线网络、数据流挖掘、计算机网络,E-mail:wzhwzh-11@163.com。
引文格式:伍转华,潘立,王永利.传感数据世系的有效压缩传输与查询方法[J].南京理工大学学报,2017,41(1):47-58.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-02-28