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Author:

Dongzhi Cao (Dongzhi Cao.) | Peng Liang (Peng Liang.) | Tongjuan Wu (Tongjuan Wu.) | Shiqiang Zhang (Shiqiang Zhang.) | Li Zhou (Li Zhou.)

Abstract:

Collaboration between IoT end‐devices and edge servers or idle devices enables offloading of computational tasks, providing an effective solution to address inherent limitations in computational resources, storage capacity, and energy efficiency. However, IoT network openness introduces security challenges, such as privacy breaches, data security, and “free‐riding” attack. Securing computational offloading is crucial for service quality and reliability. In this article, we introduce a comprehensive approach to address these challenges. First, trust metrics are performed at the level of resource requester and resource provider respectively, and the trust level of both parties is matched to reduce the adverse effects of malicious devices or servers on computing offloading. Then, a distributed decision‐making method based on game theory is designed to improve the performance of the algorithm and avoid the single‐point‐of‐failure problem through the joint participation of multiple edge servers in decision‐making. Finally, a blockchain‐based task offloading process control strategy is used to deal with the “free‐riding” attack. The results of simulation experiments show the effectiveness of our proposed offloading decision‐making method.

Keyword:

IoT edge computing game theory blockchain-based control strategy trusted offloading

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Source :

Concurrency and Computation:Practice and Experience

ISSN: 1532-0626

Year: 2023

Issue: 15

Volume: 36

Page: n/a-n/a

2 . 0 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 21

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