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Freshness-Aware Data Service Mashups

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Advances in Services Computing (APSCC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10065))

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Abstract

Data mashups provide end-users with an opportunity to create situational applications which aggregate and manipulate data from multiple diverse data sources. A challenging problem is once the data sources are updated and propagate bottom-up to the top level, how to ensure the freshness of mashups. In this paper, an approach is proposed to generate a data mashup scheme and its corresponding synchronous policy guaranteeing the optimal data freshness quality. The paper firstly applies the heuristic transformation rules to select some optimal mashup schemes, and then selects an equivalence mashup by solving the 0-1 integer programming problem. Lastly the paper applies a heuristic algorithm on the mashup scheme to get the operation nodes needed to be materialized and then the synchronous policy. This paper also reports a number of experiments studying the benefits and costs of the proposed approach.

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Notes

  1. 1.

    http://www.tpc.org/tpch/.

  2. 2.

    http://jmeter.apache.org/.

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Acknowlegments

This work is supported in part by the Key Program of Natural Science Foundation of Beijing under Grant No. 4131001.

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Authors and Affiliations

  1. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Cloud Computing Research Center, North China University of Technology, Beijing, 100144, China

    Guiling Wang & Shuo Zhang

Authors
  1. Guiling Wang
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  2. Shuo Zhang
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Correspondence to Guiling Wang .

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Editors and Affiliations

  1. Guangzhou University, Guangzhou, China

    Guojun Wang

  2. North China University of Technology, Beijing, China

    Yanbo Han

  3. University of Murcia, Murcia, Spain

    Gregorio Martínez Pérez

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Wang, G., Zhang, S. (2016). Freshness-Aware Data Service Mashups. In: Wang, G., Han, Y., Martínez Pérez, G. (eds) Advances in Services Computing. APSCC 2016. Lecture Notes in Computer Science(), vol 10065. Springer, Cham. https://doi.org/10.1007/978-3-319-49178-3_33

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  • DOI: https://doi.org/10.1007/978-3-319-49178-3_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49177-6

  • Online ISBN: 978-3-319-49178-3

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