Dynamic web worker pool management for highly parallel javascript web applications

Summary JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web...

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Published in:Concurrency and computation Vol. 28; no. 13; pp. 3525 - 3539
Main Authors: Verdú, Javier, Costa, Juan José, Pajuelo, Alex
Format: Journal Article Publication
Language:English
Published: Blackwell Publishing Ltd 10.09.2016
Subjects:
Applications programs
Arquitectura de computadors
Dynamics
HTML5
Inclusions
Informàtica
Java (programming language)
JavaScript
Mathematical models
Multithreaded
Optimization
Parallel processing (Electronic computers)
Parallelism
Pools
Processament en paral·lel (Ordinadors)
Processors
Simultaneous multithreading processors
Web applications
Web workers
Àrees temàtiques de la UPC
ISSN:1532-0626, 1532-0634
Online Access:Get full text
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Abstract Summary JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non‐optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co‐running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes. Copyright © 2015 John Wiley & Sons, Ltd.
AbstractList JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non-optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co-running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes. Peer Reviewed
JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non-optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co-running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes.
JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non‐optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co‐running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes. Copyright © 2015 John Wiley & Sons, Ltd.
Summary JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows multithreaded JavaScript web apps to exploit parallel processors. However, developers have difficulties to determine the minimum number of web workers that provide the highest performance. But even if developers found out this optimal number, it is a static value configured at the beginning of the execution. Because users tend to execute other applications in background, the estimated number of web workers could be non‐optimal, because it may overload or underutilize the system. In this paper, we propose a solution for highly parallel web apps to dynamically adapt the number of running web workers to the actual available resources, avoiding the hassle to estimate a static optimal number of threads. The solution consists in the inclusion of a web worker pool and a simple management algorithm in the web app. Even though there are co‐running applications, the results show our approach dynamically enables a number of web workers close to the optimal. Our proposal, which is independent of the web browser, overcomes the lack of knowledge of the underlying processor architecture as well as dynamic resources availability changes. Copyright © 2015 John Wiley & Sons, Ltd.
Author Pajuelo, Alex
Costa, Juan José
Verdú, Javier
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  organization: Department of Computer Architecture, BarcelonaTECH (UPC), Barcelona, Spain
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  givenname: Alex
  surname: Pajuelo
  fullname: Pajuelo, Alex
  organization: Department of Computer Architecture, BarcelonaTECH (UPC), Barcelona, Spain
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10.1145/346152.346320
10.2172/835380
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10.1007/s10723-014-9292-9
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Snippet Summary JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows...
JavaScript web applications are improving performance mainly thanks to the inclusion of new standards by HTML5. Among others, web workers API allows...
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SubjectTerms Applications programs
Arquitectura de computadors
Dynamics
HTML5
Inclusions
Informàtica
Java (programming language)
JavaScript
Mathematical models
Multithreaded
Optimization
Parallel processing (Electronic computers)
Parallelism
Pools
Processament en paral·lel (Ordinadors)
Processors
Simultaneous multithreading processors
Web applications
Web workers
Àrees temàtiques de la UPC
Title Dynamic web worker pool management for highly parallel javascript web applications
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