PPGC: A Path Planning System by Grid Caching based on Cloud-Edge Collaboration for Unmanned Surface Vehicle in IoT Systems

Unmanned Surface Vehicle (USV), as an important terminal device in IoT systems, is widely used in various fields. Path planning is one of the common problems to be solved in different USV applications. Most of the current path planning systems are deployed in the cloud, resulting in fluctuating trans-mission delay, considerable computational delay and queuing delay when processing path planning requests from multiple USVs. Furthermore, in large-scale path planning systems, the computational time spent in planning the optimal path grows exponentially with the increasing distance between the source and target location. To address these path planning problems in the cloud, we propose a Path Planning algorithm by Grid Caching (PPGC) based on Cloud-Edge collaboration. PPGC only processes path requests at the current edge servers in the areas of the USVs, and optimizes path sharing cache and the grid-based path matching algorithm to improve the promptness of the path planning response. Experimental results show that the average response latency of the proposed path planning system is reduced by 73% compared with the cloud-based path planning system.