University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Auteur Mohamed Boutine |
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Titre : Task Scheduling and Resource Management based on bio-inspired approach Type de document : texte imprimé Auteurs : Mohamed Boutine, Auteur ; Abdeslem Nadjai, Auteur ; Djamila Mechta, Directeur de thèse Année de publication : 2022 Importance : 1 vol (38 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Edge Computing
Task SchedulingIndex. décimale : 004 Informatique Résumé :
Mobile Edge computing (MEC) is a recent computing paradigm that provides lightweight cloud computing
and storage capabilities at the network’s edge. A fundamental research topic for edge computing is offloading
decisions, scheduling and resource allocation. In this paper, we formulate the computation offloading, scheduling
and resource allocation problems into a system energy-efficiency, delay and cost minimization problem by
taking into account the completion energy time and cost. We consider partial offloading and full offloading
decisions, which are implemented as workflows and bags of tasks. Then, by solving the optimization problem,
we propose a solution based on a genetic algorithm (GA) for scheduling and resource allocation. The GA
maps each task to a mobile edge computing (MEC) according to its resources and availability to reduce the
total service time and enhance the effectiveness of MEC resourcesCôte titre : MAI/0650 En ligne : https://drive.google.com/file/d/1Bq-8dcJgKDvzps365jdRU99mEVSHynLn/view?usp=share [...] Format de la ressource électronique : Task Scheduling and Resource Management based on bio-inspired approach [texte imprimé] / Mohamed Boutine, Auteur ; Abdeslem Nadjai, Auteur ; Djamila Mechta, Directeur de thèse . - 2022 . - 1 vol (38 f .) ; 29cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Edge Computing
Task SchedulingIndex. décimale : 004 Informatique Résumé :
Mobile Edge computing (MEC) is a recent computing paradigm that provides lightweight cloud computing
and storage capabilities at the network’s edge. A fundamental research topic for edge computing is offloading
decisions, scheduling and resource allocation. In this paper, we formulate the computation offloading, scheduling
and resource allocation problems into a system energy-efficiency, delay and cost minimization problem by
taking into account the completion energy time and cost. We consider partial offloading and full offloading
decisions, which are implemented as workflows and bags of tasks. Then, by solving the optimization problem,
we propose a solution based on a genetic algorithm (GA) for scheduling and resource allocation. The GA
maps each task to a mobile edge computing (MEC) according to its resources and availability to reduce the
total service time and enhance the effectiveness of MEC resourcesCôte titre : MAI/0650 En ligne : https://drive.google.com/file/d/1Bq-8dcJgKDvzps365jdRU99mEVSHynLn/view?usp=share [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0650 MAI/0650 Mémoire Bibliothéque des sciences Anglais Disponible
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