论文标题
在区块链授权的物联网中计算的内源性安全性
Endogenous Security of Computation Offloading in Blockchain-Empowered Internet of Things
论文作者
论文摘要
本文调查了用于计算物联网（IoT）计算卸载的内源性安全体系结构，该区块链技术可以使恶意行为的可追溯性，并且任务数据上传链接从传感器到小型基站（SBS）受到智能反射表面（IRS）的智能反射表面（IRS）的物理层安全性（PLS）的保护（PLS）。接收任务数据后，SBS分配了计算资源以帮助传感器执行任务。现有的计算卸载方案通常集中于网络性能改善，例如能源消耗最小化，并忽略了传感器支付的汽油费，从而导致高气付款人的不满。在这里，我们设计了一种面向气体的计算卸载方案，该方案可以保证传感器的满意度，同时旨在减少能耗。此外，我们推断出IRS辅助PLS传输的急性保密率，该速度可以代表全球保密性能分配计算资源。模拟表明，提出的计划确保支付较高天然气的节点获得更强的计算资源，并且与能源消耗最小化方案相比，筹集了$ 4 \％$ $的能源消耗。
This paper investigates an endogenous security architecture for computation offloading in the Internet of Things (IoT), where the blockchain technology enables the traceability of malicious behaviors, and the task data uploading link from sensors to small base station (SBS) is protected by intelligent reflecting surface (IRS)-assisted physical layer security (PLS). After receiving task data, the SBS allocates computational resources to help sensors perform the task. The existing computation offloading schemes usually focus on network performance improvement, such as energy consumption minimization, and neglect the Gas fee paid by sensors, resulting in the discontent of high Gas payers. Here, we design a Gas-oriented computation offloading scheme that guarantees the degree of satisfaction of sensors, while aiming to reduce 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 ensures that the node paying higher Gas gets stronger computational resources, and just raises $4\%$ energy consumption in comparison with energy consumption minimization schemes.
