Task Offloading in Trusted Execution Environment empowered Edge Computing
Yuepeng Li, Deze Zeng, Lin Gu, Andong Zhu, Quan Chen · 2020
To tackle the computation resource poorness on the end devices, task offloading is developed to reduce the task completion time and improve the Quality-of-Service (QoS). Edge computing facilitates such offloading by provisioning resources at the proximity of the end devices. Nowadays, many tasks on end devices have an urgent demand for the security of execution environment. To address this problem, we introduce trusted execution environment (TEE) to empower edge computing for secure task offloading. To explore TEE, the offloading process should be redesigned with the introduction of data encryption and decryption. This makes traditional offloading optimization policy fail to be applied directly. To address this issue, we are motivated to take the data encryption and decryption into the offloading scheduling algorithm. In particular, we propose a Customized List Scheduling based Offloading (CLSO) algorithm, aiming at minimizing the total completion time with the consideration of energy budget limitations on the end devices. The experiment results show that our approximation algorithm can effectively reduce the total completion time and significantly outperforms existing state-of-the-art offloading strategy.