This survey covers hard real-time scheduling algorithms and schedulability analysis techniques for homogeneous multiprocessor systems. It reviews the key results in this field from its origins in the late 1960s to the latest research published in late 2009. The survey outlines fundamental results about multiprocessor real-time scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, and hybrid scheduling algorithms, approaches to resource sharing, and the latest results from empirical investigations. The survey identifies open issues, key research challenges, and likely productive research directions.  Today, real-time embedded systems are found in many diverse application areas, including automotive electronics, avionics, telecommunications, space systems, medical imaging, and consumer electronics. In all of these areas, there is rapid technological progress. Companies building embedded real-time systems are driven by a profit motive. To succeed, they aim to meet the needs and desires of their customers by providing systems that are more capable, more flexible, and more effective than those of their competitors, and by bringing these systems to market earlier. This desire for technological progress has resulted in a rapid increase in both software complexity and the processing demands placed on the underlying hardware. To address demands for increasing processor performance, silicon vendors no longer concentrate wholly on the miniaturization needed to increase processor clock speeds, as this approach has led to problems with both high power consumption and excessive This work has been funded in part by the EU FP7 projects Jeopard (project number 216682) and eMuCo (project number 216378), the EU FP7 Artist Design Network of Excellence, and the EPSRC project Tempo (EP/G055548/1).
Real-time scheduling REF is relative work.
A survey of hard real-time scheduling for multiprocessor systems
CSUR
Computer Science