## 4 Mechanisms and Optimizations
### Preference-Based Scheduling Strategies
Additionally, the simulation experiment also incorporates a simulated hierarchical name resolution system designed to maintain the mapping relationship between IDs and IP addresses within the simulation environment, thereby aiding in the scheduling of computing resources in this simulation experiment. In this simulation experiment, computing resource requests and the status information of CRNs are sourced from an open dataset provided by Alibaba Cloud [55]. In terms of requests, the dataset only includes the quantity of resources requested by Users in dimensions of CPU, memory, and storage. Therefore, it can be assumed that Users have no strict constraints on bandwidth, price, scheduling delay, or computing resource service types in this simulation experiment. Regarding the status information of CRNs, the dataset offers the total amount of resources and corresponding utilization rates in terms of CPU, memory, and storage for each CRN. For subsequent performance validation, the PUE values and usage prices for each CRN are set to random values within the ranges \((1,4]\) and \((0,20]\), respectively. It is also assumed that all CRNs can provide the same computing resource service types and share identical computing resource service identifiers. Under the aforementioned assumptions, based on the request information provided by the dataset, \(5\,w/10\,w/15\,w/20\,w\) computing resource request packets are formed. These resource request packets are randomly dispatched to various SNs within the topology illustrated in Figure 7. The intervals between the arrival of each request at the SN's data plane follow an exponential distribution with a scale parameter set to \(40\,w\). The dataset's CRNs are randomly linked to the SNs corresponding to the SNs in the simulated topology, and they report resource status information to the SNs through the SNs. The SNs then exchange resource status information to form a resource status information table. For cross-level aggregation, the TOPSIS and entropy weight method are employed to select CRNs with relatively higher values in all resource dimensions, representing lower-level scheduling domains. Each SN, based on the demand information from the computing resource request packets and the state information from the resource status information table, executes the corresponding computing resource scheduling strategy to accomplish the scheduling. Detailed experimental parameter configurations are provided in Table 7 for reference. The main metrics emphasized in this simulation experiment include the success rate of scheduling and the average value of priority indicators corresponding to user \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Description** \\ \hline Topology & Network\(\times\) \\ Number of SNs & 37 \\ Number of L\({}_{3}\) scheduling domains & 9 \\ Number of L\({}_{2}\) scheduling domains & 3 \\ Number of L\({}_{1}\) scheduling domains & 1 \\ Communications delay between SNs in L\({}_{3}\) & \([1\,ms,5\,ms]\) \\ Communications delay between SNs in L\({}_{2}\) & \([5\,ms,15\,ms]\) \\ Communications delay between SNs in L\({}_{1}\) & \([15\,ms,30\,ms]\) \\ Data Set & [[https://github.com/alibaba/clusterdata](https://github.com/alibaba/clusterdata)]([https://github.com/alibaba/clusterdata](https://github.com/alibaba/clusterdata)) (accessed on 1 January 2018) \\ Number of resource request packets & \(5\,w/10\,w/15\,w/20\,w\) \\ The scale of the exponential distribution & \(40\,w\) \\ PUE of CRNs & \((1,4]\) \\ Price for the use of CRNs & \((0,20]\) \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Simulation configuration. preferences. The former refers to the proportion of successfully scheduled request packets in all request packets. In the context of distributed resource scheduling, a higher success rate of scheduling indicates a stronger capability of the scheduling architecture to address resource contention issues when the total quantity of request packets is held constant.