Scalable and Anonymous Computation Offloading Solution in Blockchain

Document Type : Original Article

Authors

1 PhD Student, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

2 School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

3 Faculty of Computer Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

Abstract

Today, with the implementation of the new generation of communication networks, we are witnessing a huge evolution in the development of the Internet of Things (IoT). The limitation in the computing power of the devices connected to this platform creates a challenge and lack of support for these devices to run programs with high computation load. Computation offloading in the edge network has been introduced as a suitable approach to deal with these limitations. Using these devices requires maintaining the privacy and security of the offloaded workload so that the sensitive and confidential information of IoT users is not compromised during the computation offloading process. For this purpose, blockchain is used. Blockchain technology has unique features such as transparency, immutability decentralization, and automated applications, which makes it a suitable option for data generated in the IoT platform. The use of blockchain in computation offloading faces limitations such as managing many requests due to the design of consensus methods. In addition, by analyzing the transactions and traffic, the influential groups can obtain the identity of the owners of the offloaded workloads and their sensitive content and violate privacy. To solve these challenges, this article takes a step forward by presenting a scalable and anonymous computation offloading method in blockchain. The proposed approach changes the blockchain architecture using the Merkel chain as a Directed Acyclic Graph and optimizes the consensus method to solve the challenges of scalability. As well, the proposed approach uses zero-knowledge proof to improve privacy and anonymity.

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TABRIZ JOURNAL OF ELECTRICAL ENGINEERING

Articles in Press, Corrected Proof
Available Online from 07 September 2024

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