## 3 Experiment  
### Experiment Setup  
To demonstrate the rationality and applicability of the proposed evaluation method, we selected the ChinaNet network from the Topology Zoo as the target for this experiment [32]. The Topology Zoo contains 261 real network topologies from around the world and is recognized by network researchers as a publicly available dataset for experimental testing, making it a valuable resource for network-related research and experiments, particularly for various network simulations. As shown in Figure 7, the topology of the ChinaNet network, which we chose as the test network for this paper, contains 42 nodes and 66 edges. The topology graph reveals the presence of both centralized key nodes and edge nodes, thus allowing us to better characterize different styles within the network. When designing the experiments, we considered the connectivity between the topology nodes and the ease of operation. We chose ONOS 2.4.1 and Mininet to build the experimental environment. Mininet allows for the flexible setup of network topology based on specific requirements, while the ONOS  
Figure 6: Schematic diagram of the third type of simplification operation. controller can automatically disseminate flow tables and control the link relationships between nodes. In the subsequent attack experiments, we could easily select the nodes to attack. We replicated the ChinaNet network in Mininet and set various parameters such as IP address, MAC address, and bandwidth according to the actual network. As shown in Figure 8, based on the actual network configuration, we divided the network topology into different heterogeneous sub-networks according to a ratio of 2:3:1:4. Since nodes in different sub-networks exhibit varying information transmission performance, we define the common transmission delay of different heterogeneous networks as different unit times, i.e., the time it takes for data to traverse a link of length 1 in the topology, based on data from Google. The node types and their corresponding transmission unit delays are defined as follows: Dark blue nodes represent wired interconnection networks with a unit delay of 20 ms. Light blue nodes represent the mobile Internet with a unit delay of 5 ms. Yellow nodes represent satellite networks with a unit delay of 100 ms. Orange nodes represent drone self-organizing networks with a unit delay of 5 ms. To achieve efficient transmission across different heterogeneous networks, we must address the protocol conversion problem. When transmitting data across heterogeneous networks, the protocol fields of packets need to be converted to meet the requirements of the destination network. Traditional protocol conversion methods typically rely on complex protocol cross-reference tables, requiring each network node to refer to the table when transmitting data. This approach not only increases computational overhead but also introduces potential conversion errors and transmission delays. Figure 7: ChinaNet network topology. (**a**) Geographic map; (**b**) PYTHON generation graph. To address these issues, we propose a cross-layer protocol encapsulation approach. Specifically, we encapsulate the protocol fields required by different heterogeneous networks uniformly in the header of the transport system message at the application layer. This method allows a network node to parse the relevant fields in the message header to complete the protocol conversion without referring to a cross-reference table when a packet enters different heterogeneous networks. This approach simplifies the protocol conversion process, reduces computational overhead, and improves the efficiency and reliability of data transmission. Under this cross-layer protocol encapsulation architecture, data traversing different heterogeneous networks requires only one parsing operation to complete the protocol conversion, avoiding delays caused by multiple conversions.