Forthcoming and Online First Articles

International Journal of Cloud Computing

International Journal of Cloud Computing (IJCC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Cloud Computing (One paper in press)

Regular Issues

  • Adaptive Online Task Scheduling Algorithm for Resource Regulation on Heterogeneous Platforms   Order a copy of this article
    by Yongqing Liu, Fan Yang, Fuqiang Tian, Jun Mou, Bo Hu, Peiyang Wu 
    Abstract: As computing technology advances, resource regulation on heterogeneous platforms has emerged as a key research area for future computing environments. In cloud task scheduling, studies focus on intelligent agent models and performance indicators that balance user experience and cost-effectiveness. Research into deep reinforcement learning and deep deterministic policy gradient (DDPG) algorithms has been conducted, incorporating heterogeneous resource regulation to address the varied needs of different data centers. Key task characteristics include length, average instruction length, and average CPU utilization, with significant standard deviations. During training, a Poisson distribution parameter with a lambda value of 1 was used, leading to convergence in the loss curve. Although the DDPG algorithm had a slightly higher virtual machine usage cost and an instruction response time of 306.5, it provided notable economic benefits, demonstrating improved management and utilization of computing resources.
    Keywords: Heterogeneous platform resource regulation; Cloud task scheduling; Deep reinforcement learning algorithm; Differences in data centre environments; Computational resource management.
    DOI: 10.1504/IJCC.2025.10070909
     

 

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