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Resource allocation and offloading decision for secure UAV-based MEC wireless-powered System
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AI
DOI：10.1007/s11276-023-03401-w.png)
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Abstract
En 中文
Unmanned aerial vehicles (UAVs) equipped with mobile edge computing (MEC) servers and featuring flexible deployment capabilities can help to reduce the computing pressure on ground user networks. However, the majority of ground users are hindered by their limited battery life, preventing them from working without interruption. To maximize the service lifetime of ground users, UAVs transmit energy to them first and then collect offload tasks afterwards. This approach allows users to work without interruption while transmitting UAVs with computing tasks which can then be processed with the help of MEC servers. This helps to reduce the pressure on ground user networks, ensuring that they remain reliable and efficient. Therefore, we propose an optimization problem that aims to maximize the minimum security offloading rate of the system. This problem involves multiple variables, so conventional methods are not suitable for solving it. Our proposed scheme utilizes block coordinate descent (BCD) and successive convex approximation (SCA) algorithms, which can better optimize the user offloading decision, energy transfer duration, and user transmit power. Numerical results demonstrate that our scheme is more effective than the two benchmark schemes in improving the system performance.
Keywords:
Wireless power transfer
Secure communication
Mobile edge computing
Resource allocation
Journal
IF:
2.1
Papers:
308
Citations:
5.4K