Failure Recovery for Network Slicing in Software-Defined Integrated Satellite-Terrestrial Networks

Network slicing in software-defined integrated satellite-terrestrial networks (SD-ISTNs) enables the creation of customized network slices on shared infrastructure, improving flexibility and resource utilization. However, node failures due to software/hardware faults, energy depletion, or attacks may disrupt slices, causing service interruptions.Failure recovery in SD-ISTNs is particularly challenging, as satellite mobility results in a time-varying yet predictable topology and the availability of multi-dimensional resources dynamically fluctuates. Therefore, in this paper, we investigate rapid failure recovery for network slicing in time-varying SD-ISTNs by jointly leveraging communication, storage, and computation resources to achieve efficient recovery and minimize the service completion time. Specifically, we employ the multi-functional time-expanded graph (MF-TEG) to model time-varying SD-ISTNs with multi-dimensional resources, and formulate the failure recovery problem as a mixed integer nonlinear programming (MINLP) problem. To effectively solve this problem, we propose two novel algorithms: (i) an effective reformulation-based mixed integer linear programming (ER-MILP) algorithm that reformulates the original MINLP into a tractable MILP and serves as a high-quality benchmark, albeit with relatively high computational complexity; and (ii) a binary-search-based penalty successive upper bound minimization-rounding (BS-PSUM-R) algorithm that achieves near-optimal performance with significantly lower complexity. Simulation results demonstrate that both algorithms effectively reduce service completion time compared with baseline algorithms.