A kind of Energy-efficient Scheduling Algorithm under the Constraint of Reliability (ESACR) for the random tasks in multiprocessor system was proposed. It would choose the processor which might consume the least energy when the task's deadline could be guaranteed. For the signal processor, Earliest Deadline First (EDF) strategy was used to schedule the tasks and all the tasks were made execute in the same voltage/frequency. When the new task could not match the deadline, the non-execution voltage/frequency of former tasks would be raised. At the same time, the recovery time was reserved for the executing task in order to promise that the task could be rescheduled when errors happened. The simulation shows that the ESACR can provide the better energy efficiency with the guarantee of system reliability , compared to Highest Voltage Energy-Aware (HVEA), Minimum Energy Minimum Completion time (ME-MC) and Earliest Finish First (EFF).

With the enhancement of computing performance in multiprocessor systems, the management of energy consumption becomes more important, and how to meet real-time constraints and effectively reduce energy consumption in the real-time scheduling is also a key issue. Based on multiprocessor computing systems, concerning randomly arrived task, On-Line Energy-Aware Scheduling Algorithm (OLEAS) was proposed. The algorithm meeting the task deadlines under the premise possibly puts the task scheduler on the least energy consumption producing processor. When a task on all the processors could not meet the deadline requirements, the part of the task between the processors shall be adjusted possibly to meet the deadline requirements. Meanwhile, OLEAS was in a bid to execute the task on a single processor according to the average voltage/frequency, thus reducing the energy consumption. When the new task did not meet the deadline requirements, the former voltage/frequency of unexecuted tasks should be one by one adjusted higher. Compared with the performance of EFF (Earliest Finish First), HVEA (Highest Voltage Energy-Aware), LVEA (Lowest Voltage Energy-Aware), MEG (Minimum Energy Greedy) and ME-MC (Minimum Energy Minimum Completion time) in simulated experiments, the final result shows OLEAS owns obviously comprehensive advantage in the aspect of meeting task deadlines and energy consumption saving.