Abstract
Cloud communication technology is Internet-based computing, where shared resources, software, information, are provided to computers and devices on-demand. They guarantee a way to share distributed resources and services that belong to different organizations through virtualization technology. Cloud has announced a modern idea by deploying one application which offers variety and a lot of services to a number of cloud-users at the same time, however, it suffers from scheduling and workload problems. This paper proposed a cloud computing task scheduling algorithm based on greedy algorithm and Antlion Optimizer algorithm. The main goal of this algorithm is to reduce the make-span and the total cost of the tasks and execution time. This paper suggested the objective share-search function of the make-span and costs of the tasks in order to improve the initialization of the pheromone, the greedy algorithm and the pheromone update method in the antlion algorithm. Also, this context illustrates the analytical study between almost used scheduling algorithms and the proposed algorithm. Theoretically, the proposed algorithm provides a more flexible and guarantee a solution to solve the problem of task scheduling in the cloud computing environment.
Highlights
The science of computing is categorized according to their usage pattern, distributed computing, grid computing, utility computing and cloud computing are famous examples of categories
This paper proposed a cloud computing task scheduling algorithm based on greedy algorithm and Antlion Optimizer algorithm
This paper suggested the objective share-search function of the makespan and costs of the tasks in order to improve the initialization of the pheromone, the greedy algorithm and the pheromone update method in the antlion algorithm
Summary
The science of computing is categorized according to their usage pattern, distributed computing, grid computing, utility computing and cloud computing are famous examples of categories. The new trends of distributed computing technology require integration between distributed computing systems and networking communication systems. The task scheduling process strives to distribute the load in equal proportions across virtual machines (VMs) depending on resources capacity so that each resource is not overload or underutilized in a cloud system [5]. This paper proposed a new type of scheduling optimizing algorithm annotated as (GALO) in which, a hybrid algorithm is used in the scheduling processes. GALO a hybrid between heuristic greedy search and Antlion to optimize scheduling based on the workload profile in virtualized environments and it makes an equal resource allocation of VMs and adapts these allocations based on the estimated cost.
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