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Optimizing makespan and resource utilization in cloud computing environment via evolutionary scheduling approach.

Faten K Karim1, Sara Ghorashi1, Salem Alkhalaf2

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Summary
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This study introduces an evolutionary algorithm-based scheduling approach for makespan optimization and resource utilization (EASA-MORU) in cloud computing. The novel technique enhances cloud performance by optimizing resource allocation and load balancing.

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Artificial Intelligence

Background:

  • Cloud computing offers on-demand resource access via virtualization, enabling shared hardware infrastructure for multiple users.
  • Resource scheduling (RS) is a critical NP-hard challenge in cloud environments, significantly impacting overall performance.
  • Metaheuristics show promise in improving cloud computing (CC) performance when applied to scheduling algorithms.

Purpose of the Study:

  • To develop an evolutionary algorithm-based scheduling approach for makespan optimization and resource utilization (EASA-MORU) in cloud environments.
  • To enhance cloud infrastructure performance through efficient resource allocation and load balancing.
  • To address the NP-hard resource scheduling problem in cloud computing.

Main Methods:

  • The study proposes the EASA-MORU technique, utilizing the dung beetle optimization (DBO) algorithm for resource scheduling.
  • The DBO technique is employed to optimize makespan and resource utilization within the cloud infrastructure.
  • The approach focuses on balancing loads and distributing resources according to dynamic cloud demands.

Main Results:

  • The EASA-MORU technique demonstrates superior performance in makespan optimization and resource utilization compared to existing methods.
  • Comprehensive comparative studies validate the effectiveness of the proposed EASA-MORU technique across various performance metrics.
  • The method effectively balances loads and distributes resources based on cloud infrastructure demands.

Conclusions:

  • The EASA-MORU technique offers an effective solution for resource scheduling challenges in cloud computing.
  • The proposed approach significantly improves cloud performance by optimizing makespan and resource utilization.
  • The dung beetle optimization (DBO) algorithm proves to be a viable metaheuristic for cloud resource scheduling.