Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments

Authors

  • Anamika Yadav Department of Computer Science and Engineering, BBD University, Faizabad Road, Lucknow, Uttar Pradesh, India 226028
  • Hridesh Varshney Department of Computer Science and Engineering, BBD University, Faizabad Road, Lucknow, Uttar Pradesh, India 226028
  • Sarvesh Kumar Department of Computer Science and Engineering, BBD University, Faizabad Road, Lucknow, Uttar Pradesh, India 226028

DOI:

https://doi.org/10.57159/gadl.jcmm.2.5.23074

Keywords:

Cloud Computing, Task Scheduling, Cloudlets, Virtual Machines (VMs), Load Balancing

Abstract

Cloud computing has become a cornerstone of modern IT infrastructure, offering scalable and flexible resources. However, efficient resource management, particularly cloudlet scheduling, presents a significant challenge due to its NP-hard nature. This paper introduces a novel heuristic-based cloudlet scheduling algorithm aimed at minimizing execution time and improving load balancing in cloud computing environments. We detail the development and implementation of the algorithm, along with a simulation setup using the CloudSim toolkit to evaluate its performance against existing methods. Results from extensive simulations demonstrate that the proposed algorithm consistently reduces turnaround times, thus optimizing resource allocation. The findings suggest that our approach can significantly impact cloud computing efficiency, paving the way for improved service provider offerings and user satisfaction. The implications of these advancements are discussed, alongside potential directions for future research in dynamic cloud environments.

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Published

31-10-2023

How to Cite

Yadav, A., Varshney , H., & Kumar, S. (2023). Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments. Journal of Computers, Mechanical and Management, 2(5), 14–21. https://doi.org/10.57159/gadl.jcmm.2.5.23074

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Section

Original Articles

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Received 2023-07-20
Accepted 2023-09-29
Published 2023-10-31