Quasi-Sobol-Based Optimization and Sigmoid Fuzzy Logic for Efficient Task Clustering in Decentralized Edge-Cloud Architectures

Year : 2025 | Volume : 12 | Issue : 02 | Page : 9 18
    By

    Dinesh Kumar Reddy Basani,

  • Rajya Lakshmi Gudivaka,

  • Sri Harsha Grandhi,

  • Basava Ramanjaneyulu Gudivaka,

  • Raj Kumar Gudivaka5,

  • M.M. Kamruzzaman,

  1. Engineer, CGI, Department of Computer Science, British Columbia, , Canada
  2. Engineer, Wipro, Department of Computer Science, Hyderabad, India
  3. Engineer, Intel, Folsom, Department of Computer Science, California, USA
  4. Engineer, Department of Computer Science, Raas Infotek, Delaware, USA
  5. Engineer, Department of Computer Science, Surge Technology Solutions Inc, Texas, USA
  6. Assistant Professor, Department of Computer Science, College of Computer and Information Sciences Jouf University, Sakakah, Saudi Arabia

Abstract

Decentralized edge-cloud systems face a lot of issues in efficient task clustering, resource allocation, and real-time decision-making. Conventional methods mostly fail to work well under dynamic workloads and uncertain conditions. This study intends to optimize task clustering through quasi-Sobol-based optimization and Sigmoid Fuzzy Logic for resource allocation, enhancing decision-making accuracy and achieving efficiency in the system at the edge-cloud environment. A hybrid technique that has incorporated optimization via Quasi-Sobol sequences along with Sigmoid Fuzzy Logic for the decision-making block has been developed. The developed approach was benchmarked against prevailing techniques and then judged regarding accuracy enhancement, precision boost, and bettering system performance. Accuracy, precision, recall, and F1-Score significantly improved, proving its efficiency in real-time task clustering and resource allocation within decentralized systems. The new method optimizes the performance of the decentralized edge-cloud environment by improving task clustering and resource allocation and provides a real-time, scalable solution for large-scale applications.

Keywords: Task clustering, edge-cloud, Quasi-Sobol optimization, sigmoid fuzzy logic, resource allocation, efficiency

[This article belongs to Trends in Machine design ]

How to cite this article:
Dinesh Kumar Reddy Basani, Rajya Lakshmi Gudivaka, Sri Harsha Grandhi, Basava Ramanjaneyulu Gudivaka, Raj Kumar Gudivaka5, M.M. Kamruzzaman. Quasi-Sobol-Based Optimization and Sigmoid Fuzzy Logic for Efficient Task Clustering in Decentralized Edge-Cloud Architectures. Trends in Machine design. 2025; 12(02):9-18.
How to cite this URL:
Dinesh Kumar Reddy Basani, Rajya Lakshmi Gudivaka, Sri Harsha Grandhi, Basava Ramanjaneyulu Gudivaka, Raj Kumar Gudivaka5, M.M. Kamruzzaman. Quasi-Sobol-Based Optimization and Sigmoid Fuzzy Logic for Efficient Task Clustering in Decentralized Edge-Cloud Architectures. Trends in Machine design. 2025; 12(02):9-18. Available from: https://journals.stmjournals.com/tmd/article=2025/view=227518


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Regular Issue Subscription Original Research
Volume 12
Issue 02
Received 15/04/2025
Accepted 25/04/2025
Published 10/06/2025
Publication Time 56 Days
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