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Applying Lagrange Model to Fill Data During Big Data Streaming

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Sustainable Communication Networks and Application (ICSCN 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 39))

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Abstract

Advancements in technology have significantly reshaped the social and economic environment. Businesses are coming up with new strategies to uncover hidden information from data in order to support better prediction and analysis. Data continues to grow at a rapid rate and it has become necessary to process the quality data. In mission critical applications, streaming of data plays a very important role. Discontinuity in data stream is unaffordable as it consumes more time and money. This paper proposes a technique through Lagrange’s Interpolation, which could avoid discontinuity in data streams when large data is being processed.

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Acknowledgement

I would like to extend my gratitude to the members of PRO-ACT who have developed the data set used in this work. PRO-ACT (Pooled Resource Open-Access ALS Clinical Trials Database) contains about 8500 records of ALS patients whose identity is hidden.

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Authors and Affiliations

  1. Jain College of Engineering and Technology, Hubli, India

    Sindhu P. Menon

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  1. Sindhu P. Menon
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Correspondence to Sindhu P. Menon .

Editor information

Editors and Affiliations

  1. Surya Engineering College, Kathirampatti, Tamil Nadu, India

    P. Karrupusamy

  2. Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan

    Joy Chen

  3. Department of Computer Science, Kennesaw State University, Kennesaw, GA, USA

    Yong Shi

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Menon, S.P. (2020). Applying Lagrange Model to Fill Data During Big Data Streaming. In: Karrupusamy, P., Chen, J., Shi, Y. (eds) Sustainable Communication Networks and Application. ICSCN 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-030-34515-0_11

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