Energy-Efficient Multicore Scheduling for Hard Real-Time Systems: A Survey

As real-time embedded systems are evolving in scale and complexity, the demand for a higher performance at a minimum energy consumption has become a necessity. Consequently, many embedded systems are now adopting multicore architectures into their design. However, scheduling on multicores is not a trivial task and scheduling to minimize the energy consumption further increases the complexity of the problem. This problem is especially aggravated for hard real-time systems where failure to meet a deadline can be catastrophic. Such scheduling algorithms yearn for a polynomial time complexity for the task-to-core assignment problem with an objective to minimize the overall energy consumption. There is now a trend toward heterogeneous multicores where cores differ in power, performance, and architectural capabilities. The desired performance and energy consumption is attained by assigning a task to the core that is best suited for it. In this article, we present a survey on energy-efficient multicore scheduling algorithms for hard real-time systems. We summarize various algorithms reported in the literature and classify them based on Partitioned, Semi-Partitioned, and Global scheduling techniques for both homogeneous and heterogeneous multicores. We also present a detailed discussion on various open issues within this domain.