Asynchronous Distributed Genetic Algorithms with Javascript and JSON

• URL: http://arxiv.org/abs/2401.17234v1
• Date: Tue, 30 Jan 2024 18:23:28 GMT
• Title: Asynchronous Distributed Genetic Algorithms with Javascript and JSON
• Authors: Juan Juli\'an Merelo and Pedro A. Castillo and Juan Luis Jim\'enez Laredo and Antonio M. Mora and Alberto Prieto
• Abstract summary: We present a distributed evolutionary computation system that uses the computational capabilities of the ubiquituous web browser. Since computing becomes a social activity and is inherently impredictable, in this paper we will explore the performance of this kind of virtual computer.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In a connected world, spare CPU cycles are up for grabs, if you only make its obtention easy enough. In this paper we present a distributed evolutionary computation system that uses the computational capabilities of the ubiquituous web browser. Using Asynchronous Javascript and JSON (Javascript Object Notation, a serialization protocol) allows anybody with a web browser (that is, mostly everybody connected to the Internet) to participate in a genetic algorithm experiment with little effort, or none at all. Since, in this case, computing becomes a social activity and is inherently impredictable, in this paper we will explore the performance of this kind of virtual computer by solving simple problems such as the Royal Road function and analyzing how many machines and evaluations it yields. We will also examine possible performance bottlenecks and how to solve them, and, finally, issue some advice on how to set up this kind of experiments to maximize turnout and, thus, performance.

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