Decentralized Blockchain-Based and Trust-Aware Task Offloading Strategy for Healthcare IoT
Junyu Ren, Tuanfa Qin
Abstract
Although smart healthcare has achieved rapid development and has gained considerable attention from academia and industry, pressing challenges exist, such as resource limitation and stringent security demand. To tackle the issues, a blockchain-based and trust-aware task-offloading strategy (BBTAS) is proposed in this work, whereby task-offloading requests are published as blockchain transactions that are automatically yet securely performed by smart contracts (SCs). An SC is a set of codes implementing predefined rules agreed by the participants involved. When a rule meets certain criteria or triggered by some events or transactions, an SC can perform by itself and generate verifiable results, which can be validated and securely stored in the blockchain. The proposed recommendation filtering method (RFM) and trust penalty measure (TPM)-based trust mechanism is powerful in resisting network insider attacks, and the inherent time-inefficiency problem of blockchain can be alleviated by integrating trust factor, which is theoretically analyzed in this work. To optimize the selection of service node, a utility-based decision-making method (UB-DMM) is proposed, which can maximize the system utility on the basis of fully considering multiple significant performance metrics of the system. Extensive simulations have been carried out to validate the effectiveness and superiority of the proposed measures.