IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v17y2025i8p348-d1714442.html
   My bibliography  Save this article

A Trusted Multi-Cloud Brokerage System for Validating Cloud Services Using Ranking Heuristics

Author

Listed:
  • Rajganesh Nagarajan

    (Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Sriperumbudur 602117, India)

  • Vinothiyalakshmi Palanichamy

    (Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Sriperumbudur 602117, India)

  • Ramkumar Thirunavukarasu

    (School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, India)

  • J. Arun Pandian

    (School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, India)

Abstract

Cloud computing offers a broad spectrum of services to users, particularly in multi-cloud environments where service-centric features are introduced to support users from multiple endpoints. To improve service availability and optimize the utilization of required services, cloud brokerage has been integrated into multi-cloud systems. The primary objective of a cloud broker is to ensure the quality and outcomes of services offered to customers. However, traditional cloud brokers face limitations in measuring service trust, ensuring validity, and anticipating future enhancements of services across different cloud platforms. To address these challenges, the proposed intelligent cloud broker integrates an intelligence mechanism that enhances decision-making within a multi-cloud environment. This broker performs a comprehensive validation and verification of service trustworthiness by analyzing various trust factors, including service response time, sustainability, suitability, accuracy, transparency, interoperability, availability, reliability, stability, cost, throughput, efficiency, and scalability. Customer feedback is also incorporated to assess these trust factors prior to service recommendation. The proposed model calculates service ranking (SR) values for available cloud services and dynamically includes newly introduced services during the validation process by mapping them with existing entries in the Service Collection Repository (SCR). Performance evaluation using the Google cluster-usage traces dataset demonstrates that the ICB outperforms existing approaches such as the Clustering-Based Trust Degree Computation (CBTDC) algorithm and the Service Context-Aware QoS Prediction and Recommendation (SCAQPR) model. Results confirm that the ICB significantly enhances the effectiveness and reliability of cloud service recommendations for users.

Suggested Citation

  • Rajganesh Nagarajan & Vinothiyalakshmi Palanichamy & Ramkumar Thirunavukarasu & J. Arun Pandian, 2025. "A Trusted Multi-Cloud Brokerage System for Validating Cloud Services Using Ranking Heuristics," Future Internet, MDPI, vol. 17(8), pages 1-15, July.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:8:p:348-:d:1714442
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/17/8/348/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/17/8/348/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:17:y:2025:i:8:p:348-:d:1714442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.