## 3 Network Architecture and System Model
### Computation Task Offloading Model
The total latency taken to offload the tasks to an LEO satellite can be expressed as follows:  
\[T_{is}^{LEO}=T_{iu}^{up}+T_{is}^{up}+T_{s}^{comp}+T_{iu}^{down}+T_{ib}^{down} \tag{9}\]  
where \(T_{iu}^{up}\), \(T_{ins}^{up}\), \(T_{isu}^{down}\), \(T_{iub}^{down}\) and \(T_{is}^{comp}\) represent the uploading latency of task \(i\) from BSs to UAVs, from UAVs to LEO satellites, the downloading latency from LEO satellites to UAVs, from UAVs to BSs, and the computation delay of task \(i\), respectively. For this paper, we ensured that the task was completed within the time delay constraints. Therefore, to allocate computing resources rationally, the node only provides the lowest possible computational resources, \(f_{i}=n_{i}^{comp}/L_{i}^{T}-T^{trans}\), where \(T_{i}^{trans}\) represents the time taken for task \(i\) to be transmitted over the link. There is an upper bound on the total amount of computing resources an ECN can have. As a result, the combined computational resources required for the tasks assigned to a node should not exceed the upper limit. \[\sum_{i=1}^{n}f_{i}x_{ib}^{BS}\leq L_{b}^{Bcomp},\forall b\in\mathcal{B}, \tag{10}\]  
\[\sum_{i=1}^{n}f_{i}x_{iu}^{UAV}\leq L_{u}^{ULoop},\forall u\in\mathcal{U}, \tag{11}\]  
\[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]0  
We consider caching in 3C, where each ECN has its individual storage limit. \[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]1  
\[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]2  
\[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]3  
\(L_{b}^{Bcache},L_{b}^{Ucache}\), and \(L_{b}^{Lcache}\) represent the cache upper bound of the BS \(b\), UAV \(u\), and LEO satellite \(s\), separately. The cost for task offloading is closely tied to the server type and the number of required computing resources. In this paper, we focus on solving computationally intensive and time-delay-sensitive tasks. Therefore, minimizing the offload cost by selecting an appropriate offloading target is crucial. Hence,  
\[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]4 \[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]5 \[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]6  
\[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]7  
In the above equation, \(C_{i}\) denotes the final cost of task \(i\); \(C^{ALL}\) denotes the cost for accomplishing whole tasks; \(\delta_{b}^{BS}\), \(\delta_{b}^{UAV}\), and \(\delta_{b}^{LEO}\) represent the ratio between the fees and the data size that will be processed by BSs, UAVs, and LEO satellites, respectively \[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]8 (18) \[x^{BS}_{ib},x^{ULAV}_{iu},x^{LEO}_{is}\in\{0,1\},b\in\mathcal{B},u\in\mathcal{ U},s\in\mathcal{S} \tag{3}\]9 (2), (3), (10), (11), (12), (13), (14), (15)