The integration of satellite and ground networks (SGIN) represents a significant advancement in the evolution of 6G mobile technologies. The rapid movement of satellites leads to swift changes in network topology. By adjusting the Service Function Chain (SFC) to these frequent changes, it's possible to diminish SFC delay and enhance the user experience. This study addresses the challenge of SFC migration within the dynamic SGIN framework. We initially developed a mathematical formulation for the VNF migration and SFC reconfiguration task, with the objective of optimizing the total system benefits. An enhanced genetic algorithm was introduced as a solution, striking an optimal compromise between SFC delay and the expenses associated with migration. When we compare our findings to previous algorithms, it's clear that our method substantially reduces the costs linked to network migration, enhances the overall profitability of services, and achieves a more favorable balance between SFC latency and migration costs.
With the advancement of satellite communication technology and space launch technology, low earth orbit (LEO) satellites have become the best choice to overcome geographical limitations and achieve global communication. In order to achieve efficient performance in the large-scale LEO constellation network, a routing algorithm adapted to satellite network is necessary. A routing algorithm based on on-demand routing is proposed to address the issues of high network overhead and difficult routing in the large-scale LEO constellation. "Maximum routing restriction area" is defined based on the satellite network structure to reduce the routing overhead in the large-scale constellation network and improve network performance. The simulation results show that this algorithm has better network performance in the large-scale constellation network compared to the other on-demand routing algorithms.
Low-orbit satellite communication has the advantages of global coverage and low latency, and the satellite network is developing in the direction of gigantism, low orbital altitude, tilted orbit, and inter-satellite link networking, which brings more challenges to the design of routing algorithms. Aiming at the characteristics of mega-constellation networks (MCNs), this paper proposes a local flooding-based survivable routing algorithm (LFSA) that obtains the local link-state information by limiting the flooding range, to reduce the flooding and computation overheads of the network. Based on the topological characteristics of MCNs, a next-hop selection mechanism based on minimum Manhattan distance is proposed. Simulation results show that the LFSA algorithm improves the pathfinding capability and reduces end-to-end delay in the face of random link failure and regional satellite failure.
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