论文标题
空间任务的自适应任务卸载:基于州政策的方法
Adaptive Task Offloading for Space Missions: A State-Graph-Based Approach
论文作者
论文摘要
太空探索的进步导致了任务的爆炸。通常,这些任务被卸载到接地服务器上,以增强计算能力,或者将相邻的低地球轨道卫星用于减少传输延迟。但是,总体延迟取决于计算和传输成本。现有的卸载方案虽然以两种费用高度优化,但对于整体绩效来说可能是糟糕的。计算传输成本困境尚未解决。 在本文中,我们提出了一种自适应卸载方案,以减少整体延迟。核心思想是在整个网络上共同建模并优化传输局限制过程。具体而言,为了表示计算状态迁移,我们将图形节点概括为具有多个状态。通过这种方式,关节优化问题被转化为状态图上的最短路径问题。我们进一步提供了一种扩展的Dijkstra算法,以进行有效的路径发现。仿真结果表明,该方案在SpaceCube v2.0上的表现分别优于地面和单跳卸载方案高达37.56%和39.35%。
Advances in space exploration have led to an explosion of tasks. Conventionally, these tasks are offloaded to ground servers for enhanced computing capability, or to adjacent low-earth-orbit satellites for reduced transmission delay. However, the overall delay is determined by both computation and transmission costs. The existing offloading schemes, while being highly-optimized for either costs, can be abysmal for the overall performance. The computation-transmission cost dilemma is yet to be solved. In this paper, we propose an adaptive offloading scheme to reduce the overall delay. The core idea is to jointly model and optimize the transmission-computation process over the entire network. Specifically, to represent the computation state migrations, we generalize graph nodes with multiple states. In this way, the joint optimization problem is transformed into a shortest path problem over the state graph. We further provide an extended Dijkstra's algorithm for efficient path finding. Simulation results show that the proposed scheme outperforms the ground and one-hop offloading schemes by up to 37.56% and 39.35% respectively on SpaceCube v2.0.