## 4 Application of Blockchain Technology in Knowledge-Based Networks
### Cloud Computing and Edge Computing  
The distribution of computer assets upon request, such as server infrastructure, memory, applications, and facilities, through the internet is identified as cloud computing. Moreover, within the cloud computing context, networking tasks can be accomplished by building cloud computing applications with guidelines for network operation virtualization and employing cloud computing equipment [376].  
In the edge network of a cloud, blockchain has been deployed in an Edge Resource Scheduling Scheme (ERSS) powered by AI and motivated by cross-domain collaboration and a transaction acceptance method differentiated by credit, which has resulted in reduced edge service costs and improved service capacities [377]. Similarly, a framework for edge-network Resource Allocation (RA) by integrating edge computing nodes and IoT devices with blockchain-based policies and transactions that provide security, dependability, and flexibility, along with a smart contract mechanism to integrate DRL for assigning edge resources, has been studied in [378]. Likewise, in order to provide secure edge services, smart contracts are used to participate in these services, and machine learning is proposed to be utilized in these services to learn from data and generate knowledge [379]. Moreover, by utilizing edge computing for workload balancing, blockchain for data sharing and transactions, and machine learning for data analysis, work in [380] shows that integration of these three technologies results in lower processing times with high security. Fuzzy logic reasoning has been leveraged for Node Selection (NS) in blockchain-based edge IoT networks in order to allocate resources and make other network decisions [381].  
A Blockchain-based Offloading and Scheduling System (OSS) is used in fog-cloud networks by modeling the offloading problem as a Markov problem solved using deep reinforcement learning and scheduling tasks, using blockchain for healthcare workloads in IoMT [382].  
In the Distributed Security Framework (DSF) presented in [383], cloud layer and edge layer collaboration is used in Power IoT. DSF leverages blockchain and federated DRL for dynamic and secure network computation offloading, where resources are allocated flexibly and data are shared securely. Furthermore, a KDN ecosystem has brought together cloud,edge, and IoT networks known as ChainFL, where blockchain and federated learning have been further utilized to provide secure and intelligent services for the orchestrated architecture [384]. Moreover, Consortium Blockchain and Deep Reinforcement Learning (CBDRL) are used to create a trusted service function chain orchestration for resource sharing in cloud-edge networks, where deep reinforcement learning is used to minimize orchestration cost [385]. Additionally, Blockchain Congestion Control (BCOOL) is a framework that controls messages using dispersed faith contract tactics based on the blockchain, where a multivariable linear regression-driven software-defined agreement approach is used to forecast traffic jams and machine learning for flexible service chaining in mixed cloud/edge vehicular networks [386]. Similarly, for cloud-edge collaborative computing-enabled networks, collective reinforcement learning is utilized for Intelligent Cloud-Edge Collaborative Resource Allocation (IC-ECRA) and result sharing, while blockchain is utilized for ensuring the authenticity of data sharing [387].