  In this paper, we investigate time-division based framework for integrated
sensing, communication, and computing in integrated satellite-terrestrial
networks. We consider a scenario, where Internet-of-Things devices on the
ground operate with sensing and communication in a time-division manner, and
can process the sensing results locally, at the edge, or in the cloud via the
satellite communication link. Based on the proposed framework, we formulate a
multi-dimensional optimization problem to maximize the utility performance of
sensing, communication, and computing abilities. After decomposing the original
optimization problem into two subproblems, we first derive the closed-form
solution of the optimal task partitioning strategy for terrestrial users and
satellite users. Then, we develop the joint subframe allocation and task
partitioning strategy to optimize the overall performance, by means of which
the Pareto optimal solutions can be obtained along the Pareto frontier.
Extensive simulations are provided to demonstrated the effectiveness of the
proposed strategy, which is 10% to 60% superior compared with the benchmarks.
Also, the trade-off between the multidimensional resource and multi-functional
performance is analyzed from the perspective of network design.
