# Resource Mapping Allocation Scheme in 6G Satellite Twin Network
## 1 Introduction
It is difficult to characterize the real-time network geometric topology range of satellite and ground nodes. The static transmission of network geometric topology characterization is that the connection between the satellite constellation and the  
Figure 1: The challenges of mapping and resource allocation in 6G satellite twin network. ground nodes is used as the input for the random simulation of communication behaviors. Although this method can simulate the discrete connectivity of the network geometric topology of the satellite constellation and the ground nodes, it also does not realize real-time interaction between the network geometric topology and communication behaviors. The synchronous transmission of network topology compression characterization is that the network topology of the satellite constellation and ground nodes is split into a series of event slices over the system cycle, in which each slice describes a fixed network topology over a period of time. This method can synchronously transfer the network topology by dividing the time slices, but the too-small slice division imposes higher requirements on the computer performance and the fidelity of real-time interaction between network geometric topology and communication behaviors. For the connectivity problem of the communication-twin-computing integration model, object standardization as middleware [16; 17], object unification as multi-agent [18; 19], service-oriented integration of objects [20; 21], microservice-independent object [22; 23], and object normalization as function [24] are generally studied. The object of normalization as middleware is to shield the differences between different hardware and software environments and provide a standard, unified transport interface to accomplish transparent access between the communication system, the twin system, and the computing system. However, this approach requires specialized transmission protocols to re-encapsulate the data of systems. The complexity and massive data in the 6G satellite twin network present challenges. Object unification as multi-agent is to view heterogeneous system data as different agents and to unify the data processing commands to act accordingly during data processing. This approach has good scalability, but a large number of agents indicate that the ground nodes can cause a slower processing speed and increase system complexity. The service-oriented integration of objects is to encapsulate the tasks into different services, providing multiple different ways to access the services for heterogeneous systems and reusing the services. However, the service-oriented architecture requires the design of a complex service framework, and it is difficult to be transparently aware of the network state. Microservices-independent object is based on service-oriented with finer granularity and lightweight framework for transmission. However, for the 6G satellite twin network with massive data, too-fine service division leads to too many services and requires efficient computer performance for support. Object normalization as a function normalizes all functions in a heterogeneous system to functions. Functions are scheduled to connect the communication system, the twin system, and the computing system. However, feature extraction and normalization of cross-platform objects are huge challenges. Facing the problem of high redundancy of resource allocation among heterogeneous systems, to meet the common demands of heterogeneous systems in computing, interaction, and storage, existing studies generally use efficient resource allocation methods such as demand resource adaptive allocation [25; 26; 27; 28], multi-objective dynamic on-demand allocation [29; 30; 31; 32], and artificial intelligence allocation [33; 34]. The demand resource adaptive allocation method schedules computational tasks, segments tasks, and manages resources to place tasks by considering parameter size, historical configuration, and running time.