Dynamic Traffic Grooming Based on Virtualization-Plane-Aided Optimization for Elastic Optical Satellite Networks  
[PERSON]  
1 School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, [EMAIL_ADDRESS] (M.Y. ); [EMAIL_ADDRESS] (ET.T)1 School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, [EMAIL_ADDRESS] (M.Y. ); [EMAIL_ADDRESS] (ET.T)1 School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, [EMAIL_ADDRESS] (M.Y. ); [EMAIL_ADDRESS] (ET.T)1 School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, [EMAIL_ADDRESS] (ET. the challenge of accommodating various services, including advanced reservation (AR) services [6]. AR services involve an unavoidable initial delay but require completion of data transmission before a specified cut-off time. Examples of such services include remote data backup and satellite high-definition video transmission [7]. The rational allocation of AR services enables users to access applications that execute in parallel while ensuring that resources are available at a specified future time [8]. Consequently, the resource allocation method for AR within a specified time range is designed to be elastic. Elastic optical satellite networks (EOSNs) rely on optical orthogonal frequency division multiplexing (O-OFDM) technology to provide finer spectrum resources, adaptive modulation formats, and flexible data transmission methods [9]. With the increasing demand for network capacity and service resilience, EOSNs have become a focal point in research, particularly in low-Earth-orbit (LEO) satellite networking. AR services in EOSNs are elastic, and unique research is needed to customize resources for these services. Service elasticity enables efficient and controllable routing and dynamic bandwidth allocation in EOSNs. The conventional architecture faces challenges such as decentralized management and predetermined link allocation, which impedes fine-grained resource management and adaptation to evolving user needs. Software-defined networking (SDN) addresses these challenges by simplifying the design, monitoring, and administration of existing networks [10]. SDN divides traditional networks into centralized control planes and remotely programmable data planes [11]. LEO satellite networks introduce SDN capabilities for managing and deploying algorithms in EOSNs [12]. Consequently, software-defined EOSNs (SD-EOSNs) [13] typically consist of three planes: the data plane, the control plane, and the application plane, which enhance management efficiency. In EOSNs, researchers have carried out research from many aspects, such as integrating network structure, establishing SDN-driven management architecture, and optimizing controller layout [14; 15; 16]. However, most of these research studies follow the network architecture design in the application scenario, respectively, and there are few types of research on the centralized resource optimization scheme based on the global network state in the software-defined optical satellite network. In addition, network virtualization technology, which abstracts physical networks into logical entities, has gained significant attention [17]. Those technologies enhance flexibility in resource allocation and scheduling. SD-EOSNs achieve a separation of the control plane from the data plane, thereby facilitating unified satellite control and significantly reducing algorithmic complexity. Leveraging SDN's network plane virtualization capabilities further lays a theoretical foundation for the algorithmic construction of the virtual plane. Consequently, SD-EOSNs emerge as an effective solution to address traffic grooming challenges in EOSNs, as substantiated by relevant literature [18].