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Storage and Management Strategy for Heterogeneous Data Stream Based on Mutation Information

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Advances in Wireless Sensor Networks (CWSN 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 334))

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Abstract

mutant information For the internet of things(IoT), how to effectively store heterogeneous data streams is a new challenge. Currently random sampling is generally used for data stream storage. Additionally B+ tree is widely used to for quickly indexing. Such data in store are random, and it ignores the users’ interest. In addition, B+ tree is applicable for one-dimension data, which is not feasible for multiple heterogeneous data streams. Herein, in this paper we propose a new sampling method to satisfy the users’ interest according to the mutant information. Besides that an extended B+ tree structure is designed for multiple heterogeneous data stream so that the user can quickly index the interested data. Extensive experiment results show that the new sampling method and the extended B+ tree work efficiently than current sampling methods and storage mechanisms.

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References

  1. Babcock, A.K., Babu, S.: Data Model and issues in data stream systems. In: Popa, L. (ed.) Proc. of the 21st ACMSIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, pp. 1–16. ACM, Madison (2002)

    Google Scholar 

  2. Araru, A., Babu, S., Widom, J.: An abstract semantics and concrete language for continuous queries over streams and relations. Technical Report, Stanford University Database Group, pp. 1–6 (2002)

    Google Scholar 

  3. Jin, C.Q., Qian, W.N., Zhou, A.Y.: Analysis and Management of Streaming Data: A Survey. Journal of Software 15(8), 1172–1182 (2004)

    MATH  Google Scholar 

  4. Zhang, D.D., Li, J.Z., Wang, W.P., Guo, L.J.: Algorithms for Storing and Aggregating Historical Streaming Data. Journal of Software 16(12), 2089–2098 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  5. Cormode, G., Muthukrishnan: An Improved Data Stream Summary: The Count-Min Sketch and its Applications. Journal of Algorithms 55(1), 58–75 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  6. Wu, C.T.: The research and realization synopsis data structure in the data stream management system. Southeast University, 12–14 (2006)

    Google Scholar 

  7. Zhuang, W.: The research and realization of the data stream management system. Nanjing University of Aeronautics and Astronautics, 5–23 (2006)

    Google Scholar 

  8. Ge, J.W., Gong, P.Q., Liu, Z.H.: Method of Storing and Indexing Historical Streaming Data. Application Research of Computers 43(8), 149–153 (2007)

    Google Scholar 

  9. Feng, G.L., Gong, Z.Q., Dong, W.J., Li, J.P.: Research of climate mutation detection of based on heuristic segmentation algorithm. Acta Physics Sinica 54(11), 5494–5499 (2005)

    Google Scholar 

  10. Garofalakis, M., Gehrke, J., Rastogi, R.: Querying and mining data streams: You only get one look. In: Proceeding of the ACM SIGMOD International Conference on Management of Data (2002)

    Google Scholar 

  11. Independent Electricity System Operator (IESO), www.ieso.ca

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Chen, J., Liu, T., Li, L. (2013). Storage and Management Strategy for Heterogeneous Data Stream Based on Mutation Information. In: Wang, R., Xiao, F. (eds) Advances in Wireless Sensor Networks. CWSN 2012. Communications in Computer and Information Science, vol 334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36252-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-36252-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36251-4

  • Online ISBN: 978-3-642-36252-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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