# Blockchain-Enabled Edge Intelligence for IoT: Background, Emerging Trends and Open Issues
## 3 Emerging Trends and Visions
### Blockchain-Enabled Incentive Mechanisms in IoT  
* _Energy Trading_: On one hand, most IoT and other edge devices are energy-constrained. On the other hand, IoT devices generate and own a huge amount of data, containing valuable information. Therefore, knowledge and energy trading between edge servers and edge nodes is a research trend in this area. [PERSON] et al. [4] proposed a novel edge intelligence framework using wireless power transfer. By exploring the permissioned blockchain, the energy and knowledge trading was secured in the proposed framework. Furthermore, [PERSON] et al. [86] designed a peer-to-peer energy trading model. An incentive mechanism was proposed for discharging electrical vehicles to boost the electric power grid. A pricing platform was further given based on a consortium blockchain. Additionally, the FL-based power management was investigated by [PERSON] et al. [87]. They proposed an AI-enabled, blockchain-based electric vehicle integration system, named AEBIS, for smart grid. The overall supply power could be balanced by demand-side devices.
* _Entities Collaboration_: Motivated by the mining reward process, collaboration design among different entities in IoT systems emerges as a popular direction in this research area. [PERSON] et al. [88] motivated the collaboration among content owners, transcoders, and receivers by the proposed framework in MEC-enabled video steaming. Besides, [PERSON] et al. [44] proposed an FL-enabled crowdsourcing framework for smart home systems, in which collaboration was motivated by the reward. Furthermore, a new proof of business consensus protocol was developed by [PERSON] et al. [89] to guarantee the incentive in blockchain-enabled federated slicing. Moreover, [PERSON] et al. [90] studied the composition process in content delivery networks. Participants were rewarded by fog entities for solving this process in multimedia service delivery.
* _Auction Mechanism_: MEC servers require incentives to execute the tasks offloaded from IoT devices. However, trustworthiness should be considered in this research direction. [PERSON] et al. [91] proposed double auction mechanisms to motivate MEC servers. Moreover, a blockchain was used to prevent record tampering from malicious edge servers.  
Table 4 summarizes the literature on incentive mechanisms in IoT and the related research directions.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Directions** & **Ref.** & **Contributions** \\ \hline \multirow{3}{*}{Authentication} & [76] & Design a group signature scheme for MEC based on blockchain. \\ \cline{2-3}  & [77] & Propose an authentication framework for participating FL nodes. \\ \cline{2-3}  & [78] & Optimize the MEC network delay with authenticity priorities. \\ \hline \multirow{2}{*}{Data Security} & [79] & Propose a secure data sharing scheme based on consortium blockchain. \\ \hline \multirow{4}{*}{Data Privacy} & [33] & Propose an MEC-based blockchain network and maximize the privacy levels. \\ \cline{2-3}  & [81] & Employ blockchain for topology protection in MEC. \\ \cline{2-3}  & [40] & Design a secure data sharing architecture based on FL for industrial IoT. \\ \cline{2-3}  & [82] & Propose a novel privacy-preserving framework for ML in industry 4.0. \\ \hline \multirow{4}{*}{Data Integrity} & [83] & Propose a UAV-based scheme to achieve integrity in IoT data acquisition. \\ \cline{2-3}  & [84] & Propose a novel blockchain and edge framework to ensure data integrity in Industry 4.0. \\ \cline{2-3}  & [85] & Design a verifiable data architecture for device failure detection in industrial IoT. \\ \hline \hline \end{tabular}
\end{table}
Table 3: Research directions and related literature on IoT security.