## 3 DC-SoC Consortium Chain Network Model  
### Overview  
In traditional centralized networks, server functions are concentrated in a limited number of peers, leading to a single-point-of-failure issue, while server peers face constraints in their capacity to concurrently process services due to hardware limitations. Consequently, blockchain systems that prioritize fairness and security adopt a peer-to-peer (P2P) network architecture. Within a P2P network, each peer possesses the capability to both receive and provide services to other peers. This approach effectively leverages substantial terminal resources and simultaneously addresses the primary shortcomings of centralized networks [14]. Blockchain performance is characterized by two dimensions: transmission rate and transmission reliability [16]. Within the network layer, these dimensions are typically manifested as peer propagation delay and data coverage, respectively. A reduced propagation delay among peers correlates with a higher transmission rate for the entire blockchain network. An increased coverage rate of block data propagation within the network leads to a more robust network state. Conversely, incomplete block propagation to numerous peers diminishes network transmission reliability, often due to instability in the propagation structure and inadequacies in peer deactivation detection mechanisms. To ensure message delivery to every peer, Fabric's P2P network employs the Gossip protocol for data dissemination. However, in the context of the contagion algorithm used in traditional Gossip protocols, achieving high data coverage necessitates enhanced network connectivity, as indicated by the number of neighbors for each peer. Given the limited processing power of each peer, this approach not only heightens the peer workload but also results in a reduction of the transmission rate when network connectivity becomes excessive. To address this challenge, we propose integrating the clustering concept to establish a rational network topology by partitioning cluster relationships among peers. This strategy not only ensures network connectivity but also minimizes the network diameter during communication among interconnected peers. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**High Transmission Efficiency**} & \multicolumn{1}{c}{**Comprehensive Propagation Coverage**} & \multicolumn{1}{c}{**Transmission Reliability**} \\ \hline Ref. [16] & ✓ & \(\times\) & \(\times\) \\ Ref. [17] & ✓ & ✓ & \(\times\) \\ Refs. [18; 19] & \(\times\) & \(\times\) & ✓ \\ Refs. [20; 21] & \(\times\) & ✓ & ✓ \\ Ours & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison with other data dissemination models. Furthermore, ensuring transmission reliability is crucial, not only through optimizing the propagation structure to enhance data coverage but also by focusing on the peers' reliability themselves. In this work, we propose adopting the concept of community detection to view the entire blockchain network as a social network. Additionally, we employ both trustworthiness and economic incentive mechanisms to assign appropriate values to each peer and identify suitable propagation targets, thereby boosting the network's robustness [26]. Building on the previously mentioned concepts, we introduce a network transaction processing model specifically designed for the federation chain environment, named DC-SoC. The operational logic of the DC-SoC model is also depicted in Figure 1, this framework operates through four phases: initial clustering, social mechanism, block dissemination, and network updates, which are triggered by timing mechanisms. Initially, at network startup, peers are clustered and segmented, with the transmission delay between each peer serving as the distance metric. Subsequently, formal block broadcasting begins, encompassing three stages: push, dynamic maintenance, and restoration.