Intelligent Optimization of Availability and Communication Cost in Satellite-UAV Mobile Edge Caching System With Fault-Tolerant Codes

Abstract

Mobile computing provides storage and computation resources of proximal devices to satisfy the real-time and low-energy communication demands of the Internet of Things (IoT). However, in the areas without terrestrial base station infrastructures, the IoT sensors have trouble implementing reliable and stable connections, which results in the difficulties of data gathering and data caching. In this paper, we consider a space-air-ground integrated mobile edge caching IoT system composed of satellite and unmanned aerial vehicles (UAVs), where LEO satellite broadcasts data, and UAVs collect the data from decentralized ground sensors. Since the sensors’ low-power property leads data loss, fault-tolerant codes are employed for availability protection. We first derive the exact expressions of system availability and communication cost for data repair and collection. Then, to address the problems of the lower availability, we exploit an intelligent optimization to determine the erasure coding parameters. Lastly, we further optimize the system parameters, i.e., communication ranges and unit power costs of UAV and decentralized sensors, to minimize the total communication cost. Simulation results show that, compared to MDS codes and regenerating codes, adaptive minimum storage regenerating (AMSR) codes with optimized parameters can significantly reduce total communication cost and maintain availability of the system.