We consider a cellular network containing $n$ nodes where nodes within a cell gossip with each other in a fully-connected fashion and a source shares updates with these nodes via a mobile drone. The drone receives source updates and shares them with nodes in the cell where it currently resides. The drone moves between cells according to an underlying continuous-time Markov chain (CTMC). We evaluate the impact of the number of cells $f(n)$, drone speed $λ_m(n)$ and drone dissemination rate $λ_d(n)$ on the information freshness of nodes in the network. We use the version age of information metric to quantify information freshness. We observe that the expected duration between two drone-to-cell service times depends on the stationary distribution of the underlying CTMC and $λ_d(n)$, but not on $λ_m(n)$. However, the version age instability makes high probability analysis for a general underlying CTMC difficult. Therefore, we focus on the fully-connected drone mobility model. Under this model, we uncover a dual-bottleneck, by leveraging stochastic equivalence between drone mobility and drone dissemination speed: the version age is constrained by the slower of these two processes. If $λ_d(n) \gg λ_m(n)$, then the version age scaling of nodes is dominated by the inverse of $λ_m(n)$ and is independent of $λ_d(n)$. If $λ_m(n) \gg λ_d(n)$, then the version age scaling of nodes is dominated by the inverse of $λ_d(n)$ and is independent of $λ_m(n)$.

翻译：我们考虑一个包含$n$个节点的蜂窝网络场景，其中同一小区内的节点以全连接方式进行八卦式通信，同时信源通过移动无人机向这些节点共享更新信息。无人机接收信源更新，并将其分享给当前所在小区内的节点。无人机根据底层连续时间马尔可夫链(CTMC)在小区间移动。我们评估小区数量$f(n)$、无人机速度$λ_m(n)$和无人机传播速率$λ_d(n)$对网络节点信息新鲜度的影响，采用版本时效性指标量化信息新鲜度。研究发现，无人机与小区两次服务之间的期望间隔时间取决于底层CTMC的稳态分布和$λ_d(n)$，但与$λ_m(n)$无关。然而，版本年龄的不稳定性使得对一般CTMC进行高概率分析较为困难。因此，我们聚焦于全连接无人机移动模型。在该模型下，通过建立无人机移动速度与传播速度的随机等价性，我们揭示了双重瓶颈效应：版本时效性受限于这两个过程中较慢者。当$λ_d(n) \gg λ_m(n)$时，节点版本年龄标度由$λ_m(n)$的倒数主导，且与$λ_d(n)$无关；当$λ_m(n) \gg λ_d(n)$时，节点版本年龄标度由$λ_d(n)$的倒数主导，且与$λ_m(n)$无关。