GA-based efficient resource allocation and task scheduling in a multi-cloud environment
by Tamanna Jena; J.R. Mohanty
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 22, No. 1/2, 2022

Abstract: Efficient resource allocation to balance load evenly in heterogeneous multi-cloud computing environment is challenging. Resource allocation followed by competent scheduling of tasks is of crucial concern in cloud computing. The number of cloud users is immense, volume of incoming job-request is arbitrary and data is enormous in cloud application. In cloud computing resources are limited; therefore it is challenging to deploy various applications with irregular capacities as well as functionalities in heterogeneous multi-cloud environment. In this paper genetic algorithm-based task mapping, followed by priority scheduling in multi-cloud environment is proposed. The proposed algorithm has two important phases, namely mapping and scheduling. We performed rigorous simulations on synthetic data for a heterogeneous multi-cloud environment. Experimental results are compared with existing first in first out (FIFO) mapping and scheduling. Validity of mapping and scheduling clearly proves better performance of the entire system in terms of makespan time and throughput.

Online publication date: Mon, 23-May-2022

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