Cloud computing is one of the emerging technologies that expands the boundaries of the internet by using centralized servers to maintain data and resources. It allows users and consumers to use various applications provided by the cloud provider, but one of the major issues is task scheduling. Task scheduling is employed for the purpose of mapping the requests of users to the appropriate resources available. This paper provides a detailed survey of the available scheduling techniques for cloud environments based on six common metaheuristic algorithms. Those algorithms are the Cuckoo Search Algorithm (CSA), Chicken Swarm Optimization (CSO), Genetic Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), and Grey Wolf Optimization (GWO). The literature is analyzed from three perspectives: task type, objectives to be optimized, simulation environment, and quality of service performance metrics. In addition, the research gaps and future directions for future investigation are presented.
Details
Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Volume
65
Issue Number
2
Keywords
Cloud
task scheduling
meta-heuristic
energy
cost
pareto optimality
single objective
weighted sum
make-span
multi- objective
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Task Scheduling in a Cloud Environment Based on Meta-Heuristic Approaches: A Survey
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