SLA-DE-RALBA: Cost-efficient dynamic enhanced resource-aware load balancing algorithm for cloud computing

Mohsin Nawaz1, Altaf Hussain1, Marran Al Qwaid2, Muazzam A. Khan Khattak3

  1. Department of Computer Science, KICSIT Campus, Institute of Space Technology, Islamabad
    44000, Pakistan
    mohsin_mscs@kicsit.edu.pk, altaf.hussain@ist.edu.pk (corresponding author)
  2. Department of Computer Science, College of Computing and Information Technology, Shaqra University, Saudi Arabia
    maldossari@su.edu.sa
  3. Computer Science Department, Quaid i Azam University, Islamabad, Pakistan
    muazzam.khattak@qau.edu.pk

Abstract

Cloud computing has become a dominant paradigm for delivering scalable and flexible on-demand resources; however, efficiently executing high performance computing (HPC) workloads remains challenging, particularly in heterogeneous environments. Conventional static scheduling methods often lead to poor resource utilization and increased makespan, while dynamic approaches improve load distribution but introduce significant overhead due to continuous monitoring and real-time decision-making. To address these challenges, this paper proposes an SLA-aware Dynamic Enhanced Resource-Aware Load Balancing Algorithm (SLA-DE-RALBA). The algorithm minimizes load imbalance by considering the computational capacities of virtual machines and ensures Service Level Agreement (SLA) compliance through a three-tier priority-based workflow. The proposed approach is evaluated using CloudSim Plus on two benchmark datasets: Heterogeneous Computing Scheduling Problem (HCSP) instances and the Google Cloud Jobs dataset. Results demonstrate that SLA-DE-RALBA consistently outperforms baseline algorithms, including RALBA, DRALBA, DE-RALBA, SLA-RALBA, Dynamic Max-Min, PSSLB, and PSSELB, across key metrics such as makespan, resource utilization, job rejection, throughput, execution time, and cost. Notably, it achieves zero job rejection, reduces energy consumption by up to 85%, improves resource utilization by 11.9%, lowers makespan by 41–45%, and decreases execution time by up to 57%, making it a robust and efficient solution for HPC workload scheduling in cloud environments.

Key words

Cloud Computing, HPC Workload Scheduling, SLA-Aware Load Balancing, Dynamic Resource Management, Heterogeneous Cloud Environments

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS260523040N

Publication information

Volume 23, Issue 4 (September 2026)
Year of Publication: 2026
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

Download Available in PDF
Portable Document Format

How to cite

Nawaz, M., Hussain, A., Al Qwaid, M., Khattak, M.A.K.: SLA-DE-RALBA: Cost-efficient dynamic enhanced resource-aware load balancing algorithm for cloud computing. Computer Science and Information Systems, 23(4) (2026). https://doi.org/10.2298/CSIS260523040N