Abstract
The Rapid advancement of the satellite industry offers unprecedented opportunities for enabling Internet of Everything (IoE) applications over satellite networks. A key characteristic of such applications is that computation cannot begin until the entire application data has been fully received at the destination. To meet strict end-to-end delay constraints, minimizing the total application delay is essential. However, this requirement violates the optimal substructure property commonly assumed in traditional shortest path routing problems. Existing routing solutions often overlook these unique computation constraints and rely on substructure-preserving heuristics, resulting in suboptimal delay performance. Moreover, they lack reliability in producing delay-guaranteed routing solutions, which leads to low task completion ratios under stringent application deadlines. To overcome this problem, we propose FlexSatIoE-a routing scheme that allows for flexible buffering data over satellite networks. FlexSatIoE formulates this routing problem as an integer linear programming (ILP) problem, to provide the optimal solution. As the network scales, considering the computational intractability of ILP, FlexSatIoE further modifies the storage time-aggregated graph to comprehensively model the satellite networks' compute, storage and transmission resources. Based on the graph extension, FlexSatIoE designs an efficient routing algorithm, enabling flexible use of buffer resources by using a flow reassignment mechanism. We conduct extensive experiments over the setting of real-world satellite networks. The results show that FlexSatIoE reduces the average delay and increases the number of completed tasks by up to 50% and 40%, respectively, as compared to the existing schemes, demonstrating the superior capability and reliability of FlexSatIoE in ensuring deterministic application delays.