Boosting Bandwidth Convergence: Optimizing Resource Allocation in Satellite-Terrestrial Integrated Networks.

Satellite-Terrestrial Integrated Network (STIN) is a multidimensional network that integrates satellites and terrestrial netwoks, providing information services globally. However, facing time-varying network topology and transmission resources, STIN is limited by the uneven network resources in each network segment. Therefore, it is difficult for STIN to achieve optimal network performance during data transmission. In response to the above challenges, this paper proposes a soft-defined STIN based multipath selection and resource allocation method. We build a soft-defined network architecture for STIN, establish satellite-terrestrial dynamic network topology, and deploy distributed controller nodes. The proposed method models multiple factors that affect throughput performance in the network as a link transmission cost matrix, defining bandwidth resources, computing resources, and latency parameters for modeling. Finally, construct the optimal resource objective function for soft-defined STIN. Meanwhile, we propose a Boosting Bandwidth Convergence (BBC) method. This method merges all transmission paths using a recursive method, and obtains the optimal objective function solution. STK, Mininet, and Ryu are adopted as a joint simulation platform to simulate the three-layer network architecture of soft-defined STIN. The simulation results show that the proposed method outperforms default Ryu switch algorithm and Shortest Path Bridging (SPB) algorithm in terms of throughput, even in the presence of network interference. It exhibits comparable average delay but maintains consistent delay throughout the transmission process, unlike the fluctuating delays observed in the other two algorithms due to buffer accumulation.