Titre : |
Task Scheduling and Resource Allocation in Cloud, Fog, and Edge Environment |
Type de document : |
texte imprimé |
Auteurs : |
Azeddine Belilita, Auteur ; Iheb Ammardjia, Auteur ; Djamila Mechta, Directeur de thèse |
Année de publication : |
2022 |
Importance : |
1 vol (41 f .) |
Format : |
29cm |
Langues : |
Français (fre) |
Catégories : |
Thèses & Mémoires:Informatique
|
Mots-clés : |
Cloud Computing
Fog Computing |
Index. décimale : |
004 Informatique |
Résumé : |
n recent years, continuous developments in the Internet of Things (IoT) generate large amounts of
data, which put pressure on Cloud computing’s infrastructure. The proposed Fog and Edge computing architecture are
considered the next generation of Cloud Computing for meeting the requirements posed by the IoT devices. In such
a system, the task scheduling and resource allocation optimization is a critical problem due to the massive amount of
heterogeneous IoT tasks and resources. In this thesis, we applied the Quantum firefly algorithm (QFA), which imitates
social behaviour of fireflies mating in nature, laws of quantum physics, and laws of natural evolution to optimize resource
allocation and task scheduling for both Bag-of-Tasks and workflow applications in a cloud fog edge environment. The
experimental results show that QFA outperforms TCaS, BLA, and FCFS by up 41.2%, 42.8% and 50.9%, respectively,
in terms of cost and makespan together in the Bag-of-Tasks scenario and outperforms FCFS in the tasks workflow
scenario by 75.3%. |
Côte titre : |
MAI/0649 |
En ligne : |
https://drive.google.com/file/d/1GKYbaghaxhtB8Tzr-4sMGd2YINQMznVT/view?usp=share [...] |
Format de la ressource électronique : |
pdf |
Task Scheduling and Resource Allocation in Cloud, Fog, and Edge Environment [texte imprimé] / Azeddine Belilita, Auteur ; Iheb Ammardjia, Auteur ; Djamila Mechta, Directeur de thèse . - 2022 . - 1 vol (41 f .) ; 29cm. Langues : Français ( fre)
Catégories : |
Thèses & Mémoires:Informatique
|
Mots-clés : |
Cloud Computing
Fog Computing |
Index. décimale : |
004 Informatique |
Résumé : |
n recent years, continuous developments in the Internet of Things (IoT) generate large amounts of
data, which put pressure on Cloud computing’s infrastructure. The proposed Fog and Edge computing architecture are
considered the next generation of Cloud Computing for meeting the requirements posed by the IoT devices. In such
a system, the task scheduling and resource allocation optimization is a critical problem due to the massive amount of
heterogeneous IoT tasks and resources. In this thesis, we applied the Quantum firefly algorithm (QFA), which imitates
social behaviour of fireflies mating in nature, laws of quantum physics, and laws of natural evolution to optimize resource
allocation and task scheduling for both Bag-of-Tasks and workflow applications in a cloud fog edge environment. The
experimental results show that QFA outperforms TCaS, BLA, and FCFS by up 41.2%, 42.8% and 50.9%, respectively,
in terms of cost and makespan together in the Bag-of-Tasks scenario and outperforms FCFS in the tasks workflow
scenario by 75.3%. |
Côte titre : |
MAI/0649 |
En ligne : |
https://drive.google.com/file/d/1GKYbaghaxhtB8Tzr-4sMGd2YINQMznVT/view?usp=share [...] |
Format de la ressource électronique : |
pdf |
|