Nowadays, multi-core processing systems have to perform complex functionalities on densely packed multi-million gate platforms, making design issues like resource usage efficiency, energy consumption, temperature management of cores, etc. more challenging to handle. Since many of these processing platforms use batteries as their primary source of energy and are prone to an uncontrolled surge in temperatures, researchers have started focusing on these criteria in great detail. In this work, we propose a three-phase hierarchical resource allocation strategy called RESET for scheduling periodic tasks with a bounded number of migrations and context-switches. The first phase divides time into distinct intervals/windows based on deadlines of tasks. The exact proportional fairness needed for the progress of task executions is maintained at all window boundaries. The second phase performs energy-aware task-to-core assignments based on task execution requirements and operating frequency levels of cores. In the last phase, it splits tasks based on an input parameter $\delta$ and prepares a temperature-aware schedule for individual cores. Our experimental analysis shows that the presented strategy improves upon the state-of-the-art in terms of resource utilisation and reduces dynamic energy consumption and the average temperature of cores in the system.

如今，多核处理系统必须在密集包装的数百万个门平台上执行复杂的功能，这使得处理诸如资源使用效率，能耗，内核温度管理等设计问题变得更具挑战性。由于许多此类处理平台都将电池用作其主要能源，并且容易受到温度不受控制的波动，因此研究人员已开始非常详细地关注这些标准。在这项工作中，我们提出了一种称为RESET的三相分层资源分配策略用于调度具有有限数量的迁移和上下文切换的定期任务。第一阶段根据任务的期限将时间分为不同的时间间隔/窗口。任务执行进度所需的确切比例公平性在所有窗口边界处均保持不变。第二阶段根据任务执行要求和内核的工作频率级别执行能量敏感的任务到内核的分配。在最后一个阶段，它根据输入参数拆分任务$\delta$并为各个内核准备一个温度感知计划。我们的实验分析表明，所提出的策略在资源利用方面改进了现有技术，并降低了动态能耗和系统中核心的平均温度。