(3.239.33.139) 您好!臺灣時間:2021/03/02 16:39
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:任哲晨
研究生(外文):Che-Chen Jen
論文名稱:感測器服務、網路服務與複雜事件處理之整合
論文名稱(外文):Integrating Sensor Services and Web Services with Complex Event Processing
指導教授:李允中李允中引用關係
口試日期:2017-07-26
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:資訊網路與多媒體研究所
學門:電算機學門
學類:網路學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:44
中文關鍵詞:物聯網物聯網中介軟體複雜事件處理複雜事件處理系統時間區間網路服務
外文關鍵詞:Internet of ThingsIoT MiddlewareComplex Event ProcessingCEP SystemTemporal IntervalWeb services
相關次數:
  • 被引用被引用:0
  • 點閱點閱:45
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
近日,物聯網的研究與相關產業如日中天,從智慧家電、到手機應用軟體等, 可以看到各種不同領域都嘗試與物聯網結合,以因應日漸複雜的、更貼近使用者 的需求。然而目前物聯網的發展,並未有一個完整的一般解決方案。為此,我們 提出一套完整的物聯網系統,能夠從資料的搜集,事件的轉換,複雜事件模式的 偵測,並將事件模式轉換為商業流程的元件,同時能與使用者互動並產生回饋, 最後以應用情境來驗證整個完整的流程。
在本次的研究中,將實作複雜事件處理引擎,同時引進時間區段的概念,以強 化複雜事件處理引擎能夠處了複雜度。此外,並將收集的資料由僅針對感測器服 務,擴展至各式網路服務,同時發展公共位址與私人位址兩種系統以因應不同的 需求。最後,我們實作將複雜事件轉換成服務,與商業流程元件進行結合,進一 步完整整個物聯網系統。
Recently, researches of IOT middleware and related products have grown widely. From smart home products to mobile applications, we can see that many differ- ent domains try to integrate with IOT middleware in response to satisfy user’s requirement. However, the development of IOT middleware until now, there is no completely general solution. Thus, we give a total solution for IOT middleware, which includes data collection, event’s transformation, complex event’s detection, transforming complex event processing to services for BPEL( Business Process Execution Language) system and interacting with users. Finally, a scenario is used for verifying the whole process of IOT middleware solution.
In this research, we will implement complex event processing engine, and intro- duce the concept of the time interval in order to strengthen the complexity which complex event processing engine can handle. Besides, by integrating sensor services and web services, developing public IP and private IP for the interoperation system so as to fit requirements. Then, we implement the complex event processing transformation and integrate with BPEL system, to further complete the entire Internet of things system.
致謝 i
Acknowledgments ii
摘要 iii
Abstracts iv List of Figures viii
List of Tables ix
Chapter 1 Motivation 1
Chapter 2 Related Work 4
2.1 EventType ................................ 4
2.2 ComplexEventProcessing........................ 5
2.2.1 ComplexEventPattern ..................... 5
2.2.2 CEPEngine: NFA-based..................... 7
2.2.3 CEPEngine: Tree-based..................... 8
2.3 InformationFlowofDataProcessingModel . . . . . . . . . . . . . . 10
2.4 TemporalInterval............................. 13
2.5 PerformanceEvaluationFramework................... 13
Chapter 3 Complex Event Processing 15
3.1 BatchIterator............................... 15
3.2 KleeneClosureOperator......................... 17
3.3 TemporalIntervalOperators....................... 17
Chapter 4 CEP System Design and Implementation 24
4.1 DatatoEventTransformationRefactor. . . . . . . . . . . . . . . . . 25
4.2 WebservicesintegrationwithCEP ................... 28
4.3WebServicesIntegrationwithInteroperation. . . . . . . . . . . . . . 30
4.4 CEPservicestransformation....................... 32
Chapter 5 Experimental Evaluation 34
5.1 ScenarioVerification ........................... 34
5.2 PerformanceEvaluation ......................... 36
Chapter 6 Conclusion 39
Bibliography 41
[1]  Oracle complex event processing performance. http://www.oracle. com/technetwork/middleware/complex-event-processing/overview/ cepperformancewhitepaper-128060.pdf. Accessed: 2016-07.
[2]  Tibco.
[3]  A. Adi, D. Botzer, G. Nechushtai, and G. Sharon. Complex event processing for financial services. In Services Computing Workshops, 2006. SCW’06. IEEE, pages 7–12. IEEE, 2006.
[4]  J. Agrawal, Y. Diao, D. Gyllstrom, and N. Immerman. E cient pattern matching over event streams. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pages 147–160. ACM, 2008.
[5]  J. F. Allen. Maintaining knowledge about temporal intervals. Commun. ACM, 26(11):832–843, Nov. 1983.
[6]  O. Alonso, M. Gertz, and R. Baeza-Yates. On the value of temporal information in information retrieval. SIGIR Forum, 41(2):35–41, Dec. 2007.
[7]  P. Bizarro. Bicep-benchmarking complex event processing systems. In Dagstuhl Seminar Proceedings. Schloss Dagstuhl-Leibniz-Zentrum fu ̈r Informatik, 2007.
[8]  L. Brenna, A. Demers, J. Gehrke, M. Hong, J. Ossher, B. Panda, M. Riedewald, M. Thatte, and W. White. Cayuga: a high-performance event processing engine. In Proceedings of the 2007 ACM SIGMOD international conference on Management of data, pages 1100–1102. ACM, 2007.
[9]  H.-L. Bui. Survey and comparison of event query languages using practical examples. Ludwig-Maximilians Universit ̈at Mu ̈nchen thesis, 2009.
[10]  S. Chakravarthy and D. Mishra. Snoop: An expressive event specification language for active databases. Data Knowl. Eng., 14(1):1–26, Nov. 1994.
[11]  S. Chandrasekaran, O. Cooper, A. Deshpande, M. J. Franklin, J. M. Hellerstein, W. Hong, S. Krishnamurthy, S. R. Madden, F. Reiss, and M. A. Shah. Telegraphcq: Continuous dataflow processing. In Proceedings of the 2003 ACM SIGMOD Interna- tional Conference on Management of Data, SIGMOD ’03, pages 668–668, New York, NY, USA, 2003. ACM.
[12]  G. Cugola and A. Margara. Processing flows of information: From data stream to complex event processing. ACM Comput. Surv., 44(3):15:1–15:62, June 2012.
[13]  Q. X. Do, W. Lu, and D. Roth. Joint inference for event timeline construction. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Lan- guage Processing and Computational Natural Language Learning, EMNLP-CoNLL ’12, pages 677–687, Stroudsburg, PA, USA, 2012. Association for Computational Linguistics.
[14]  EsperTech. Event proceesing and cep platform. http://www.espertech.com/esper/.
[15]  O. Etzion and P. Niblett. Event processing in action. Manning Publications Co., 2010.
[16]  D. Gyllstrom. On supporting kleene closure over event streams.
[17]  D. Gyllstrom, E. Wu, H.-J. Chae, Y. Diao, P. Stahlberg, and G. Anderson. Sase: Complex event processing over streams. arXiv preprint cs/0612128, 2006.
[18]  W.-C. Hsieh. From data to service: An event-driven approach. Master’s thesis, National Central University, Taiwan (R.O.C.), 2014.
[19]  D. Luckham. The power of events. Addison-Wesley Reading, 2002.
[20]  A. Mathew. Benchmarking of complex event processing engine-esper. Technical re- port, Technical Report IITB/CSE/2014/April/61, Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Maharashtra, India, 2014.
[21]  Y. Mei and S. Madden. Zstream: a cost-based query processor for adaptively de- tecting composite events. In Proceedings of the 2009 ACM SIGMOD International
Conference on Management of data, pages 193–206. ACM, 2009.
[22]  M. Mendes, P. Bizarro, and P. Marques. A framework for performance evaluation of complex event processing systems. In Proceedings of the second international
conference on Distributed event-based systems, pages 313–316. ACM, 2008.
[23]  M. R. Mendes, P. Bizarro, and P. Marques. A performance study of event processing systems. In Technology Conference on Performance Evaluation and Benchmarking, pages 221–236. Springer, 2009.
[24]  Oracle. Event proceesing. http://www.oracle.com/technetwork/middleware/complex-event-processing/.
[25]  S. Rozsnyai, J. Schiefer, and A. Schatten. Concepts and models for typing events for event-based systems. In Proceedings of the 2007 inaugural international conference on Distributed event-based systems, pages 62–70. ACM, 2007.
[26]  S. Suhothayan, K. Gajasinghe, I. Loku Narangoda, S. Chaturanga, S. Perera, and V. Nanayakkara. Siddhi: A second look at complex event processing architectures. In Proceedings of the 2011 ACM workshop on Gateway computing environments, pages 43–50. ACM, 2011.
[27]  D. Wang, E. A. Rundensteiner, H. Wang, and R. T. Ellison III. Active complex event processing: applications in real-time health care. Proceedings of the VLDB Endowment, 3(1-2):1545–1548, 2010. [28]  F. Wang, S. Liu, P. Liu, and Y. Bai. Bridging physical and virtual worlds: complex event processing for rfid data streams. In International Conference on Extending Database Technology, pages 588–607. Springer, 2006.
[29]  E. Wu, Y. Diao, and S. Rizvi. High-performance complex event processing over streams. In Proceedings of the 2006 ACM SIGMOD international conference on Management of data, pages 407–418. ACM, 2006.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔