## 6 Performance Analysis and Discussion  
The experiments have shown that IDENE outperforms existing multipath forwarding schemes such as NetCodCCN and BestRoute in terms of pipeline transmission, content acquisition time, transmission delay, and other metrics. In this section, we further analyze and discuss the evaluation results. Unlike the conventional NDN forwarding procedure, IDEANE can prevent the aggregation of interest messages in PIT from different requesters who demand content with the same name by distinguishing distinct identities. Therefore, IDEANE can improve the interest efficiency, reduce encoded block redundancy, and fully use idle transmission paths. At the same time, the content can be returned to the corresponding requesters along the request paths of the interest messages differentiated with the carried identity information. Both network coding and multi-identifier networks aim to improve the network transmission efficiency. The former focuses on the computing bandwidth, while the latter focuses on the storage bandwidth. All network nodes can encode the received data packets through linear network coding instead of copying and forwarding them as in traditional networks. When receiving a series of decoded packets, i.e., linear independence encoded packets with the same number of source data segments, the receiver decodes them to obtain the required data. Using encoding in named data networks and multi-identifier networks can enable internal network nodes to simultaneously compute, store, and forward data packets, effectively utilizing multiple paths in the network, simplifying the design of interest message sending and transmission on the receiving pipeline, and reducing the complexity of cache coordination [37]. Network coding can simultaneously transmit multiple information streams on one link, which improves link utilization. The network throughput can be improved whether on a multicast or unicast system, with uniform links or non-uniform links. In addition, network coding can effectively utilize idle paths, distribute network traffic to a broader network, and balance the network load, which helps to solve problems such as network congestion [38]. Linear network coding and edge computing play complementary roles. The edges in edge computing refer to computing and storage resources on the network's edge, which can be edge servers, router gateways, etc. The problem of the limited resources of Industrial Internet objects can be solved by encoding and decoding at edge nodes. In edge computing, the original data and sensitive user privacy information will be shared or stored in edge nodes. Hence, security assurance becomes a crucial challenge in this distributed edge network framework. Since the edge node receives the encoded block instead of the original data packet, data leakage can be avoided to a certain extent, and the security of data transmission and the information security requirements of the data of both parties participating in the computation can be guaranteed. Network coding has certain reliability in the application of wireless network security. A random network coding detection strategy for data packets is generated based on network coding. This method has a small amount of computing, and the detection probability can be adjusted according to factors such as the communication control overhead, network coding complexity, and detection time At the same time, the multi-identifier network (MIN-IIoT) can establish user identity certificates and perform lightweight identity verification through the carried identity identifier and location identifier information, thereby ensuring that user identities are authorized. During network transmission, there may be abnormal interruptions, and the BestRoute strategy requires recalculation of the optimal path, resulting in network latency.