Abstract
Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.
Highlights
The Cloud Computing provides computational resources such as the Virtual Machines (VM) to Cloud users on-demand basis [1,2,3]
The MINMIN has the highest makespan amongst the algorithms under consideration
The results obtained from the CloudSim simulation environment shows that, Global League Championship Algorithm (GBLCA) scheduling algorithm performs moderately better than the MINMIN, MAXMIN, Genetic Algorithm (GA) and the Ant Colony Optimization (ACO) algorithms throughout the experiment
Summary
The Cloud Computing provides computational resources such as the Virtual Machines (VM) to Cloud users on-demand basis [1,2,3]. GBLCA: A Secure Scientific Applications Scheduling Technique for Cloud Computing Environment minimize the makespan time. The extraordinary increase in the amount of the solution search space produced by the LCA and the superior results produced by the scheme when compared with other metaheuristic algorithms motivates this research to solve scheduling problem in IaaS Cloud computing environment. This research presents a novel scientific application tasks scheduling technique for the Cloud computing service using a Global League Championship Algorithm (GBLCA) optimization technique which is a continuation and improvement of our earlier presented research [16,17], but with new improved methods and results. The remaining sections of manuscript is organized as follows: the second Section discuses the related works which includes recent literatures and techniques in scientific application scheduling in Cloud Computing, the third Section explains the global scheduling problem and the fourth Section describes the design process of the proposed GBLCA based application scheduling technique. The seventh and eighth Sections present the experimental setup and, results and discussion respectively, while the ninth Section chronicles the conclusion and recommendations
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