Energy-Efficient and Physical Layer Secure Computation Offloading in Blockchain-Empowered Internet of Things

TL;DR

This paper proposes an energy-efficient, secure computation offloading scheme for blockchain-enabled IoT that considers Gas fees and uses IRS-assisted physical layer security to optimize resource allocation and enhance secrecy.

Contribution

It introduces a Gas-oriented offloading scheme that accounts for Gas dissatisfaction and derives an ergodic secrecy rate for IRS-assisted PLS, addressing limitations of existing methods.

Findings

Lower energy consumption compared to existing schemes

Ensures higher Gas payments correlate with stronger computational resources

Effectively measures secrecy performance in IRS-assisted channels

Abstract

This paper investigates computation offloading in blockchain-empowered Internet of Things (IoT), where the task data uploading link from sensors to a base station (BS) is protected by intelligent reflecting surface (IRS)-assisted physical layer security (PLS). After receiving task data, the BS allocates computational resources provided by mobile edge computing (MEC) servers to help sensors perform tasks. Existing blockchain-based computation offloading schemes usually focus on network performance improvements, such as energy consumption minimization or latency minimization, and neglect the Gas fee for computation offloading, resulting in the dissatisfaction of high Gas providers. Also, the secrecy rate during the data uploading process can not be measured by a steady value because of the time-varying characteristics of IRS-based wireless channels, thereby computational resources allocation with a secrecy rate measured before data uploading is inappropriate. In this paper, we design a Gas-oriented computation offloading scheme that guarantees a low degree of dissatisfaction of sensors, while reducing energy consumption. Also, we deduce the ergodic secrecy rate of IRS-assisted PLS transmission that can represent the global secrecy performance to allocate computational resources. The simulations show that the proposed scheme has lower energy consumption compared to existing schemes, and ensures that the node paying higher Gas gets stronger computational resources.