This article discusses the principles, mechanisms, and strategy of hard real-time task scheduling appropriate for mobile terminal equipment. Mobile terminals have timeliness requirements for completing hard real-time tasks and also clear energy-management requirements. Therefore, this study attempts to schedule tasks under these two constraints to achieve an optimal level of energy savings. First, terminal equipment operating time and standby time should meet the maximum requirements, and second, all tasks should meet the constraints of real-time parallel scheduling. We propose a scheduling strategy based on grouping according to the latest cut-off time, with each group adopting a dynamic optimization strategy to make scheduling decisions. The feasibility and validity of this algorithm are demonstrated through experiments and simulations.
KeywordsMobile terminal, real-time task scheduling, earliest deadline first scheduling, optimal energy saving, step-by-step optimization strategy
Research backgroundResearch status of real-time task scheduling based on intelligent terminal systems Mobile intelligent terminals that run a number of hard real-time tasks that must be completed within the specified time have relatively high requirements for realtime task scheduling. Failure to meet these requirements can result in the malfunction of systems such as traffic control systems and medical monitoring systems. Periodic real-time tasks must be executed once during each fixed period of time. For example, the signal analysis and diagnosis task of a medical monitoring system is a periodic real-time task. Given a task-scheduling algorithm, if the execution of each task can be completed within its deadline, the task scheduling is denoted as feasible. The earliest-deadline-first (EDF) scheduling algorithm determines the order in which tasks are run according to the deadline of task completion such that tasks with the earliest deadlines are run first.1 The least-leisure-time-first (LSF) algorithm assigns the highest priority to the task with the shortest deadline to ensure that the most urgent tasks are executed first. Based on the EDF algorithm, Vrimani et al.2 proposed a new scheduling