## 2 Related Work
### Computing Network and Service Scheduling  
Since the concept of the Computing Network was proposed, Chinese network operators have led extensive research on such networks and published a series of white papers. In terms of standardization, relevant international research groups have published many relevant documents covering the requirements, architecture, transmission protocols, routing mechanisms, and security of Computing Networks. Table 1 summarizes some representative documents.  
As for the work within academia, current research mainly focuses on the overall architecture [24; 25; 26] and the key technologies [4; 27; 28]. As the core of the Computing Network, scheduling in Computing Networks involves selecting the 'best' cluster based on the network and computing resource status, with the definition of 'best' varying by request requirements. Currently, most research focuses on resource scheduling, essentially a resource allocation problem solved with optimization algorithms. There are few studies on service scheduling, and the results from resource scheduling cannot be directly applied to them. This is because service scheduling focuses on whether requests meet requirements and are successfully executed, rather than predicting or concerning itself with resource amounts.  
The authors in [29] proposed a Bkd-tree-based service optimization algorithm considering the response time, cost, availability, and success rate. However, the study only designed the algorithm, without detailed architecture or mechanism design. The authors in [30] proposed a FaaS Computing Network architecture integrating serverless [31] technologies but focused mainly on the macro-level structure, without adequately addressing specific service requirements. Some researchers [5; 13; 32; 33] have proposed an SRv6-based overlay service anycast system, but the technical details and performance test results are lacking, making their works largely hypothetical. The authors in [34] presented a service-based forwarding mechanism via programmable data planes to optimize service access within a single domain, but their research faces scalability issues and only supports simple operations, limiting the exploration of its potential for advanced service scheduling. This paper [35] proposes a Controlled Service Scheduling Scheme (CS3) for managing power and service distribution in SDN-based IoT environments. However, this approach is not suitable for large-scale environments and increases the processing time. The authors in [36] addressed the routing optimization problem for time-sensitive (TS) flows in software-defined Low-Earth-orbit (LEO) satellite networks. A longest continuous path (LCP) algorithm was proposed to optimize path computation. The authors in [37] addressed the controller placement and assignment problem in software-defined Low-Earth-Orbit (LEO) satellite networks for 6G, focusing on network management services. The author in [38] addressed the challenges posed by disruptive mobile applications and proposed a series of protocols and algorithms designed to manage user and service mobility at the network edge, specifically leveraging ICN and SDN. Other studies [39; 40] only conducted prospects or feasibility analysis on service scheduling without in-depth research. However, through the collation of the above research, we can conclude that it is feasible and beneficial to apply programmable data plane technology to service scheduling [4; 25; 41]. Further discussion will be carried out in the next section.  
In addition, since the previous resource scheduling is not suitable for service scheduling, new algorithms are also an issue that needs to be considered. Service scheduling involves selecting a suitable cluster from a bunch of candidate clusters. This problem is similar to cloud service selection [42], so the multi-criteria decision-making [43] (MCDM) algorithm that is often used in cloud service selection is a good choice.