## 3 Proposed Blockchain and Digital Twin-Based Heuristic Multi-Cooperation Scheduling Framework
### Blockchain-Based Data Validation
Therefore, the communication from the edge layer to the fog layer can be easily encrypted because DT is directly related to the Physical Twin (PT), and the corresponding DT can easily decrypt the data from the corresponding PT when the data in DT needs to make decisions from the headquarters, it only sends the encrypted processing results to the headquarters outside of the DT and applies them to decisions. The readability and data significance of the result information is very low for external data thieves. In addition,because the data of industrial importance is only transmitted in the fog layer composed of multiple DTs, only the internal members related to SM have access to the traffic, which is not necessary to be sent outside, so the security of the data transmission is guaranteed. ## 4 Evaluation and Performance

For our research, the most important thing is to evaluate the authenticate time of the Blockchain consensus algorithm and the precision and speed of decision-making at headquarters. ### Experience Setup

Instead of a real blockchain, we are using a simulated blockchain with simulated data. We analyze the proposed framework using Ubuntu 18.04 and an i7 processor with 32 GB RAM. The Blockchain network on the edge layer is built utilizing the Hyperledger Fabric 1.3. Virtual Cloud and Edge nodes are generated using VMware 14. ### Performance Analysis

In this section, the efficiency of the blockchain network is evaluated. We mainly focus on the authentication time, which refers to the time required to complete the consensus, and the transmission delay from the device layer to the edge layer after the consensus is achieved. Transaction throughput refers to the maximum number of transactions completed per unit of time. A transaction generator with adjustable frequency generates transactions randomly, and the number of transactions sent within the statistical time is controllable. When the transaction throughput is measured, random transactions are continuously generated at a specific rate until the number of transactions sent within the statistical time is greater than the number of transactions recorded on the block within the same time. Then, the transaction throughput is obtained by averaging. As shown in Table 3, we created two simulated commercial blockchains, one deployed in a LAN Fabric and the other deployed in a WAN Fabric. A blockchain TPS of 365.9 for the LAN and 76.4 for the WAN are used. In a WAN environment, network nodes across physical regions, network operators, and public cloud nodes generate network delay and limited network bandwidth. As a result, the transaction throughput of a WAN Fabric decreases, which is about 20.89% of that of a LAN Fabric. As shown in Figure 4, the experimental results prove the feasibility of using Blockchain technology in this architecture. The proposed solution has lower latency and faster authentication speed than the classical POW algorithm. The faster authentication speed is mainly due to the improvement of the proposed algorithm. All participants will send the request to participate in the consensus to the base station and log their identity information to the base station. After calculating the hash value in the consensus algorithm, the base station will prioritize verifying the nearest node according to the geographical location during the broadcast. This distance results in much lower communication latency. In addition, since the cross-tier transmission must be encrypted, the lightweight algorithm is more efficient than the benchmark algorithms, such as RSA and DES, regarding computation rate and transmission rate. Therefore, the Telehash algorithm deployed in the device and edge layer's transmission medium also provides lower transmission delay. Thus, the network expansion of the protocol is better with the continuous expansion of the network, more time can be saved, and lower authentication delay means higher SM efficiency, because more time can be used to process computation tasks.