Abstract:
The unmanned aerial vehicle (UAV) equipped with mobile-edge computing (MEC) can act as an air base station to provide computing services for Artificial Intelligence of Th...Show MoreMetadata
Abstract:
The unmanned aerial vehicle (UAV) equipped with mobile-edge computing (MEC) can act as an air base station to provide computing services for Artificial Intelligence of Things (AIoT) devices in remote areas. However, the computation offloading process poses a risk to users’ privacy due to potential information leaks resulting from interactions between UAVs or migration of data between AIoT devices and UAVs. In this article, we proposed a secure aerial computing network that integrates MEC and blockchain technologies to effectively guarantee privacy and security during computation offloading between AIoT devices and UAVs. Additionally, taking into account task offloading scheduling, radio spectrum resource allocation, and computation resource allocation, a joint optimization problem is formulated to minimize the weighted sum of delay and energy consumption throughout the entire computing process. To tackle this issue, we proposed a block coordinate descent (BCD)-based algorithm to solve the mixed-integer and nonconvex problem. Simulation results demonstrate that the proposed algorithm surpasses other baseline approaches.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 1, 01 January 2024)