D-Choices Scheduling: A Randomized Load Balancing Algorithm for Scheduling in the Cloud
Due to the growing popularity of the Internet, the availability of more powerful computing resources along with the lowering costs of computation and communication, the emphasis of computing has been pushed in recent years from PCs to Cloud-centric. Cloud computing has gained its popularity
from its ability to deliver various software and hardware resources as services to consumers over the Internet. However, scheduling of job or task requests to appropriate resources for execution of the applications in a Cloud environment is still an NP-complete problem. In this paper, a simplified
randomization-based load balancing algorithm is proposed to solve the job scheduling problem in Cloud computing environment. The algorithm is to dynamically allocate jobs to resources in order to minimize the job execution time and maximize resource utilization by distributing workloads evenly
among resources in the Cloud. In our algorithm, the allocation of jobs to resources is decided after examining a small number of the available servers sampled at random. The performance of the proposed D-CSA technique is extensively evaluated through conducting several simulation experiments
over a wide range of instances. Simulation results show that our approach can achieve significant reductions in makespan and balance the workload on large-scale Cloud systems.
Keywords: Cloud Computing; Job Scheduling; Load Balancing; Resource Allocation
Document Type: Research Article
Affiliations: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China
Publication date: 01 September 2017
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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