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The Performance Analysis of Web Applications Using Parallel.js Library

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Advances in Systems Engineering (ICSEng 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 364))

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Abstract

To increase the performance of web applications, programmers are increasingly turning to parallel programming. The main question of this paper is whether the most popular Parallel.js library performs better than other parallel processing solutions available. Other questions are concerned with the conditions under which Parallel.js offers the best performance gains as well as its advantages and disadvantages.

The review of literature indicated that there is no research regarding Parallel.js library and similar libraries. Similar libraries were chosen based on state of art review which suggests that the most similar libraries to Parallel.js are Operative.js for the client-side of application and Hurried for the server-side. Web Workers were also chosen to compare if those libraries are better than their base technology.

To answer the stated questions, experiments with Parallel.js and similar libraries were conducted. Experiments were divided into client-side and server-side categories. Client-side experiments were performed for Web Workers, Parallel.js and Operative.js libraries and on two web browsers with different JavaScript engines: Google Chrome and Mozilla Firefox. The server-side experiments were performed for Web Workers, Parallel.js and Hurried libraries on Node.js JavaScript environment.

The results showed that Parallel.js library is the best of all those tested only for the client-side of the application. On the server-side, the performance of Parallel.js is ranked in the middle between the other two tested technologies. The results also revealed that Parallel.js is best for task-based data processing rather than performing calculations. It was noticed that the best performance is achieved for number of Web Workers equal to number of CPU cores and for Google Chrome.

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Notes

  1. 1.

    DocumentObjectModel.

  2. 2.

    Only few experiments had uncertainty of measure higher than 5% of base measure, so this difficulty has no impact on overall results.

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Author information

Authors and Affiliations

  1. Nokia Solutions and Networks, Wrocław, Poland

    Karolina Malanowska

  2. Wrocław University of Science and Technology, Wrocław, Poland

    Ziemowit Nowak

Authors
  1. Karolina Malanowska
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  2. Ziemowit Nowak
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Correspondence to Ziemowit Nowak .

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Editors and Affiliations

  1. Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, Wrocław, Poland

    Leszek Borzemski

  2. Department of Electrical and Computer Engineering, Howard R. Hughes College of Engineering, University of Nevada, Las Vegas, USA

    Henry Selvaraj

  3. Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, Wrocław, Poland

    Jerzy Świątek

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Malanowska, K., Nowak, Z. (2022). The Performance Analysis of Web Applications Using Parallel.js Library. In: Borzemski, L., Selvaraj, H., Świątek, J. (eds) Advances in Systems Engineering. ICSEng 2021. Lecture Notes in Networks and Systems, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-030-92604-5_40

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