SEASA: Security and Energy Aware Scheduling Algorithm for Task Workflow in Mobile Edge Computing

For mobile devices with limited resources, how to efficiently execute various complex mobile applications is a huge challenge. The development of mobile edge computing (MEC) technology provides a solution to this problem and users can offload some tasks to edge servers. However, intermediate data is frequently transmitted between edge servers, which may lead to the loss, theft, or tampering of intermediate data by malicious users, ultimately affecting the output results of the workflow. Therefore, we propose a security and energy aware scheduling algorithm (SEASA) for task workflow in the MEC. The goal of the SEASA is to minimize the energy consumption of mobile devices under makespan constraint, storage constraint and the risk probability constraint. First, we construct three security strategy pool to improve the Security of the intermediate data. Second, we model the security scheduling problem of workflow and propose makespan, storage overhead and risk probability models. Finally, we use particle swarm optimization (PSO) algorithm to solve the workflow scheduling problem. In the process of coding, the task execution order, scheduling position and security service selection are considered. The experimental results indicate that our proposed method can improve the security and reduce the energy consumption of mobile devices.