Dependency-Aware Task Scheduling in TrustZone Empowered Edge Clouds for Makespan Minimization

Abstract

Task offloading to edge servers has become a promising solution to tackle the computation resource poverty of the end devices. However, the zero-trust edge computing platform is highly challenged by the growing concern on security and privacy. Thus, Trust Execution Environment (TEE), like TrustZone, is advocated to empower edge clouds to enable secure task offloading. To explore TrustZone, the inevitable involvement of data encryption and decryption operations makes existing offloading strategies not applicable any more, especially when the task dependency is considered. In addition, TrustZone has distinguishable task scheduling paradigm as one CPU core does not allow multitask coexist at the same time. Taking the above issues into consideration, we investigate a dependency-aware task offloading problem for makespan minimization in TrustZone empowered edge clouds. By inventing an extended graph to describe the task execution process, we provide a formal statement to the problem and prove its NP-hardness. We then propose a Customized List Scheduling (CLS) based approximate algorithm and theoretically analyze its achievable performance. Extensive testbed based experiment results show that our approximation algorithm can effectively reduce the makespan and significantly outperforms existing state-of-the-art offloading approaches in TrustZone empowered edge clouds.