# Blockchain-Enabled Edge Intelligence for IoT: Background, Emerging Trends and Open Issues
## 3 Emerging Trends and Visions
### Blockchain-Enabled IoT Communications  
* _5G and beyond_: Although the 5G network improves services for IoT communications [57], it may not be capable of enabling new IoT applications, including telemedicine, haptic communication, bio-IoT, etc. [PERSON] et al. [58] provided some future directions for IoT communication in 6G systems. In terms of blockchain-enabled edge intelligence, there are multiple research directions related to IoT communications. For 5G and beyond, [PERSON] et al. [59] discussed blockchain and FL particularly. Potential application scenarios were listed in this paper, including intelligent transportation, mobile networks, network data analysis, etc. Moreover, IoT automation could be realized by 6G-enabled MEC. [PERSON] et al. [16] pointed out research challenges in terms of IoT-enabled 6G devices. Furthermore, [PERSON] et al. [13] discussed the function of blockchain in 5G and beyond networks in-depth. * _Decentralized D2D:_ For blockchain-enabled edge intelligence, device-to-device (D2D) communication is a feasible solution for data sharing and collaboration. Furthermore, blockchain gives the feature of decentralization to D2D. Particularly, [PERSON] et al. [60] investigated ultra-dense wireless networks (UDNs). A decentralized computation offloading platform was proposed to coordinate tasks among devices and edge servers. Furthermore, [PERSON] et al. [47] studied cache sharing for data delivery. To assist MEC based offloading for inter-domain traffic, they proposed a blockchain-enabled market to motivate both D2D and MEC nodes. Plus, a partial Practical Byzantine Fault Tolerance protocol was proposed to minimize latency and guarantee the confidence level of the D2D sharing. * _Edge Computing_: The tradeoff between limited resources and required latency is a major challenge for edge computing. To deal with this issue, [PERSON] et al. [61] considered the collaboration of edge and cloud. They proposed an energy-efficient IoT task offloading algorithm for blockchain-enabled edge computing. Additionally, [PERSON] et al. [62] studied crowd-intelligence. An ecosystem was designed for trustless and hybrid human-machine crowd-intelligence. [PERSON] et al. [63] further investigated edge service migration. A blockchain-based secure edge service migration, namely Falcon, was proposed to extend the service scalability and flexibility. Furthermore, [PERSON] et al. [64] presented a trust-aware IoT data economic system (TIDES). The trading process in MEC systems was entirely based on the smart contract. Furthermore, [PERSON] et al. [65] optimized the allocation of limited radio and computational resources. The scheduling of block producers was considered in this resource allocation. Furthermore, fast transaction writing and maximum mining revenue should be considered separately according to different IoT device requirements. A blockchain-based offloading strategy was given for the above scenarios in MEC systems [66]. * _Edge Caching_: Content caching is a popular solution to the ever-increasing IoT data traffic. [PERSON] et al. [67] gave the offloading mode selection and caching strategy for wireless blockchain networks. A novel MEC-enabled wireless blockchain framework was further given for computation offloading and content caching [68]. Besides, ultra-reliable communication is a popular trend. [PERSON] et al. [69] used neural-blockchain for ultra-reliable caching in drone networks. Additionally, [PERSON] et al. [70] implemented FL for content caching in edge computing. A novel compressed algorithm of the FL approach, namely CREAT, was proposed for this edge caching case. * _Distributed Network Function Virtualization_: As a fundamental technology of software-defined industrial IoT [71; 72], network function virtualization (NFV) has emerged in blockchain-enabled edge intelligence recently. Distributed NFV offers a flexible way for large scale IoT networks management. [PERSON] et al. [73] proposed a blockchain-based framework to reach consensus across different management and orchestration systems.