https://hal-cea.archives-ouvertes.fr/cea-01846864Legout, V.V.LegoutECE - Department of Electrical and Computer Engineering [Blacksburg] - Virginia Tech [Blacksburg]Jan, M.M.JanDACLE-LIST - Département d'Architectures, Conception et Logiciels Embarqués-LIST - LIST (CEA) - Laboratoire d'Intégration des Systèmes et des Technologies - DRT (CEA) - Direction de Recherche Technologique (CEA) - CEA - Commissariat à l'énergie atomique et aux énergies alternativesPautet, LaurentLaurentPautetTélécom ParisTechScheduling algorithms to reduce the static energy consumption of real-time systemsHAL CCSD2015Algorithms Criticality (nuclear fission) Economic and social effects Embedded systems Energy efficiency Energy utilization Integer programming Interactive computer systems Multiprocessing systems Scheduling Scheduling algorithms Semiconductor device manufacture Hard real-time Mixed criticalities Mixed integer linear program Multi processor architecture Multi processor scheduling Multiprocessor scheduling algorithms Semiconductor technology Static consumption Real time systems[SPI] Engineering Sciences [physics]Le Roy, Léna2018-07-23 08:01:182022-02-17 10:08:062018-07-23 08:01:18enJournal articles10.1007/s11241-014-9207-71Energy consumption is an important concern when designing embedded systems. Static consumption now dominates dynamic consumption as the semiconductor technology moves to deep sub-micron scale. This has lead to the availability of energy efficient low-power states for processors. However, integrating their use at the scheduling level to reduce the energy consumption of real-time systems requires to appropriately optimize the length of the idle periods, while still ensuring real-time constraints. This problem has not been well studied when some or all the tasks are hard real-time and are executed over a multiprocessor architecture. In this paper, we propose the first optimal multiprocessor scheduling algorithms to efficiently use the low-power states of multiprocessor architectures. We target both hard real-time systems and mixed-criticality (MC) systems, in which some tasks have a lower criticality and can therefore tolerate some deadline misses. We use a similar off-line approach for both type of systems, where the idle time is modeled using an additional task. A mixed integer linear program is then used to compute schedules that optimize the length of the idle periods, such that the most efficient low-power states can be used. On-line, we extend an existing scheduling algorithm to increase the length of the existing idle periods. Simulations show that while processors are idle, we reduce the energy consumption up to ten times while keeping the number of preemptions similar to state-of-the-art optimal multiprocessor real-time schedulers. For MC systems, a trade-off between consumption reduction and deadline misses of the low-criticality tasks can be explored.