Cost-effective and Low-complexity Non-constrained Workflow Scheduling for Cloud Computing Environment

Célestin Tshimanga Kamanga*, Emmanuel Bugingo, Simon Ntumba Badibanga, Eugène Mbuyi Mukendi, Olivier Habimana

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Cloud computing possesses the merit of being a faster and cost-effective platform in terms of executing scientific workflow applications. Scientific workflow applications are found in different domains, such as security, astronomy, science, etc. They are represented by complex sizes, which makes them computationally intensive. The main key to the successful execution of scientific workflow applications lies in task resource mapping. However, task-resource mapping in a cloud environment is classified as NPcomplete. Finding a good schedule that satisfies users' quality of service requirements is still complicated. Even if different studies have been carried out to propose different algorithms that address this issue, there is still a big room for improvement. Some proposed algorithms focused on optimizing different objectives such as makespan, cost, and energy. Some of those studies fail to produce lowtime complexity and low-runtime scientific workflow scheduling algorithms. In this paper, we proposed a non-constrained, low-runtime, and low-time-complexity scientific workflow scheduling algorithm for cost minimization. Since the proposed algorithm is a list scheduling algorithm, its key success is properly selecting computing resources and its operating CPU frequency for each task using the maximum cost difference and minimum cost-execution difference from the mean.

Original languageEnglish
Pages (from-to)371-379
Number of pages9
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Issue number1
StatePublished - 2023
Externally publishedYes


  • Workflow scheduling
  • difference from the mean
  • low complexity
  • resource management
  • weighted sum difference


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