research-article

Trust‐aware task load balancing in multi‐access edge computing based on blockchain and a zero trust security capability framework

Authors:

Mark A. Gregory,

Shuo LiAuthors Info & Claims

Transactions on Emerging Telecommunications Technologies, Volume 34, Issue 12

https://doi.org/10.1002/ett.4845

Published: 10 December 2023 Publication History

Abstract

The need for low‐latency service support at the network edge has increased due to new applications such as autonomous vehicles, facial recognition, and augmented reality. Multi‐access edge computing (MEC) has emerged as a promising component of next‐generation 5G and 6G networks that provides additional storage and computing capacity at the network edge to enhance application performance, load balancing, and reduce latency. Security challenges remain, and a zero trust security framework has the potential to reduce risk and improve visibility. A zero trust management module is introduced to authenticate users after a successful registration. This article presents a three‐layer MEC model implementing a trust‐aware load balancing decision process. A Q‐learning algorithm is used to estimate trust values. Task trust and indirect trust relationships are recorded using blockchain technology. Blockchain will enable a transparent and secure mechanism that contributes to secure resource management in an MEC environment. The results provided by a framework simulation highlight the improved security outcome.

Graphical Abstract

This contribution presents a novel framework combining blockchain, Q‐learning, and Zero Trust Management Module (ZTMM) for secure MEC load balancing. It uses Q‐learning to introduce an Edge Authenticator (EA) for trust estimation and load‐balancing decisions based on server capability. The approach ensures trustworthiness validation via blockchain, incorporates ZTMM for UE identity validation, and demonstrates Proof‐of‐Concept (PoC) experiments validating security‐enhanced, trust‐aware load balancing in dynamic MEC environments.

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Cited By

Krishna Sowjanya KMouleeswaran S(2025)Enhancing cloud security with intelligent load balancing and malicious request classificationCluster Computing10.1007/s10586-024-04754-328:1Online publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1007/s10586-024-04754-3
Daah CQureshi AAwan IAdalat OKonur S(2024)Advancing IAM in the Finance Sector by Integrating Zero Trust and Blockchain TechnologyMobile Web and Intelligent Information Systems10.1007/978-3-031-68005-2_7(83-99)Online publication date: 18-Aug-2024
https://dl.acm.org/doi/10.1007/978-3-031-68005-2_7

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Trust‐aware task load balancing in multi‐access edge computing based on blockchain and a zero trust security capability framework
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Published In

cover image Transactions on Emerging Telecommunications Technologies

Transactions on Emerging Telecommunications Technologies Volume 34, Issue 12

December 2023

301 pages

EISSN:2161-3915

DOI:10.1002/ett.v34.12

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© 2023 The Authors. Transactions on Emerging Telecommunications Technologies published by John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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John Wiley & Sons, Inc.

United States

Publication History

Published: 10 December 2023

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Cited By

Krishna Sowjanya KMouleeswaran S(2025)Enhancing cloud security with intelligent load balancing and malicious request classificationCluster Computing10.1007/s10586-024-04754-328:1Online publication date: 1-Feb-2025
https://dl.acm.org/doi/10.1007/s10586-024-04754-3
Daah CQureshi AAwan IAdalat OKonur S(2024)Advancing IAM in the Finance Sector by Integrating Zero Trust and Blockchain TechnologyMobile Web and Intelligent Information Systems10.1007/978-3-031-68005-2_7(83-99)Online publication date: 18-Aug-2024
https://dl.acm.org/doi/10.1007/978-3-031-68005-2_7

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