TY - GEN
T1 - SQGA
T2 - 18th IEEE International Wireless Communications and Mobile Computing, IWCMC 2022
AU - Belmahdi, Raouf
AU - Mechta, Djamila
AU - Harous, Saad
AU - Bentaleb, Abdelhak
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Fog computing represents an extension of the Cloud infrastructure, which allows the improvement of the performance of IoT applications. The problem of task scheduling represents a challenge in this type of environment, with the aim of how to allocate the tasks to the different nodes of the Fog-Cloud infrastructure, in order to minimize makespan, cost, response time, and energy. In this paper, we propose SQGA - an algorithm to improve the workflow scheduling in Fog-Cloud environment. This algorithm is based on the quantum genetic algorithm QGA and aims to improve the makespan of applications deployed in the Fog-Cloud computing environment. The proposed SQGA scheduling algorithm is compared to the classical genetic algorithm and the First Come First Served algorithm. The experiment results show that the proposed SQGA algorithm is more efficient in makespan, and adapts better to the available resources.
AB - Fog computing represents an extension of the Cloud infrastructure, which allows the improvement of the performance of IoT applications. The problem of task scheduling represents a challenge in this type of environment, with the aim of how to allocate the tasks to the different nodes of the Fog-Cloud infrastructure, in order to minimize makespan, cost, response time, and energy. In this paper, we propose SQGA - an algorithm to improve the workflow scheduling in Fog-Cloud environment. This algorithm is based on the quantum genetic algorithm QGA and aims to improve the makespan of applications deployed in the Fog-Cloud computing environment. The proposed SQGA scheduling algorithm is compared to the classical genetic algorithm and the First Come First Served algorithm. The experiment results show that the proposed SQGA algorithm is more efficient in makespan, and adapts better to the available resources.
KW - Cloud Computing
KW - Fog Computing
KW - IoT
KW - Makespan
KW - Quantum genetic algorithm
KW - Tasks scheduling
UR - http://www.scopus.com/inward/record.url?scp=85135292018&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135292018&partnerID=8YFLogxK
U2 - 10.1109/IWCMC55113.2022.9825324
DO - 10.1109/IWCMC55113.2022.9825324
M3 - Conference contribution
AN - SCOPUS:85135292018
T3 - 2022 International Wireless Communications and Mobile Computing, IWCMC 2022
SP - 131
EP - 136
BT - 2022 International Wireless Communications and Mobile Computing, IWCMC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 30 May 2022 through 3 June 2022
ER -