This is an extension of the source code in https://github.com/harshitgupta1337/fogsim to allow the implementation of a distributed populartiy-based placement strategy. This extension has been implemented for the research presented in the article "A lightweight decentralized service placement policy for performance optimization in fog computing", accepted for publication in "Journal of Ambient Intelligence and Humanized Computing".
The details can be found in the article: https://doi.org/10.1007/s12652-018-0914-0
Code generated by Carlos Guerrero.
Please consider to cite this work as:
@Article{Guerrero2018,
author="Guerrero, Carlos
and Lera, Isaac
and Juiz, Carlos",
title="A lightweight decentralized service placement policy for performance optimization in fog computing",
journal="Journal of Ambient Intelligence and Humanized Computing",
year="2018",
month="Jun",
day="15",
abstract="A decentralized optimization policy for service placement in fog computing is presented. The optimization is addressed to place most popular services as closer to the users as possible. The experimental validation is done in the iFogSim simulator and by comparing our algorithm with the simulator's built-in policy. The simulation is characterized by modeling a microservice-based application for different experiment sizes. Results showed that our decentralized algorithm places most popular services closer to users, improving network usage and service latency of the most requested applications, at the expense of a latency increment for the less requested services and a greater number of service migrations.",
issn="1868-5145",
doi="10.1007/s12652-018-0914-0",
url="https://doi.org/10.1007/s12652-018-0914-0"
}Acknowledgment:
This research was supported by the Spanish Government (Agencia Estatal de Investigación) and the European Commission (Fondo Europeo de Desarrollo Regional) through Grant Number TIN2017-88547-P (AEI/FEDER, UE).