Dependent Task Scheduling for Multiple Applications in Mobile Edge Computing

Mobile Edge Computing (MEC) offers computational services near data sources to meet numerous real-time data processing demands of end devices. Scheduling dependent tasks in resource-constrained environments is a key research focus in MEC, aimed at enhancing the completion rates of applications within their deadlines. However, most existing works overlook the resource competition among requests arriving at different times, leading to decreased application completion rates. In this paper, we propose a dependent task online scheduling approach for multiple applications to optimize application completion rates. For multiple applications with deadline constraints, where tasks within each application may have dependencies, we propose a multi-priority task sequencing algorithm to determine the execution order of tasks. To accommodate scenarios where requests arrive at different times, we introduce a priority-based queue to dynamically adjust task execution order based on urgency and resource demands. Finally, by comparing with baseline approaches, experimental results demonstrate that our approach can improve the application completion rate by approximately 41.02%, demonstrating its effectiveness.