JOURNAL ARTICLE

Cloud Computing Task Scheduling using Genetic Algorithm: A Survey

Abstract

Cloud computing has become a hot research topic due to the robust development and migration of many services to this cloud environment. The main problem that appears is regarded with both management's efficiency and the large amount of resources utilization. These resources are managed by data centers as well as distributed to internet users dynamically depending on their availability, request and quality parameters that are in request to be usable. Thus, task scheduling is a major concern that can affect system performance. This study presents a survey of employing genetic algorithm for task scheduling in cloud environments. This survey provides a comprehensive overview of task scheduling approaches in cloud environments, with a particular focus on the application of genetic algorithms. It discusses fundamental cloud computing concepts, scheduling criteria, and classification of scheduling methods. Furthermore, it analyses a wide range of GA-based scheduling algorithms, comparing their performance, task characteristics, and simulation tools.

Keywords:
Computer science Cloud computing Scheduling (production processes) Task (project management) Genetic algorithm Machine learning Mathematical optimization Operating system Mathematics Engineering

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Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems

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