Energy-driven proportional fair scheduling for industrial measurement devices

Real-time scheduling in systems with energy or power constraints is challenging. Especially when a mixture of real-time and best effort tasks exist, it is difficult to guarantee that all deadlines are met and at the same time that the system does not run out of energy. This is the case for industrial instrumentation for hazardous areas, such as explosive atmospheres. A frequently used method of protection against explosion is intrinsic safety. That means, the power supply as well as the energy that is stored in the device is kept below a critical threshold. As a result, energy is a much scarcer resource than processing time in this class of systems. Therefore, it is appropriate to base the scheduling decision on the available and the consumed energy instead of the processing time. In this work, we adapt the Earliest-Eligible-Virtual-Deadline-First algorithm (EEVDF) for energy-driven scheduling using dynamic power management. The resulting system is hard real-time capable, takes the energy consumption of peripherals and sensors into account and utilizes slack energy efficiently and predictably. Since the scheduler guarantees the availability of sufficient energy for real-time tasks, the design of the system is significantly simplified.

[1]  Hakan Aydin,et al.  Energy-constrained scheduling for weakly-hard real-time systems , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[2]  Xue Liu,et al.  Power-Aware CPU Utilization Control for Distributed Real-Time Systems , 2009, 2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium.

[3]  Binoy Ravindran,et al.  Utility Accrual Real-Time Scheduling Under the Unimodal Arbitrary Arrival Model with Energy Bounds , 2007, IEEE Transactions on Computers.

[4]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks-the single node case , 1992, [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications.

[5]  Hussein M. Abdel-Wahab,et al.  A proportional share resource allocation algorithm for real-time, time-shared systems , 1996, 17th IEEE Real-Time Systems Symposium.

[6]  Giuseppe Lipari,et al.  Using resource reservation techniques for power-aware scheduling , 2004, EMSOFT '04.

[7]  Fei Li,et al.  Competitive analysis of online real-time scheduling algorithms under hard energy constraint , 2010, Real-Time Systems.

[8]  Attila Bilgic,et al.  Low-power smart industrial control , 2011, 2011 Design, Automation & Test in Europe.

[9]  Ana Sokolova,et al.  Power-aware temporal isolation with variable-bandwidth servers , 2010, EMSOFT '10.

[10]  Lothar Thiele,et al.  Proactive Speed Scheduling for Real-Time Tasks under Thermal Constraints , 2009, 2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium.

[11]  Tei-Wei Kuo,et al.  Voltage-scaling scheduling for periodic real-time tasks in reward maximization , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[12]  W.J. Kaiser,et al.  The low power energy aware processing (LEAP) embedded networked sensor system , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[13]  Riccardo Bettati,et al.  Delay Analysis in Temperature-Constrained Hard Real-Time Systems with General Task Arrivals , 2006, 2006 27th IEEE International Real-Time Systems Symposium (RTSS'06).

[14]  Rami G. Melhem,et al.  Dynamic and aggressive scheduling techniques for power-aware real-time systems , 2001, Proceedings 22nd IEEE Real-Time Systems Symposium (RTSS 2001) (Cat. No.01PR1420).

[15]  Chenyang Lu,et al.  Hybrid supervisory utilization control of real-time systems , 2005, 11th IEEE Real Time and Embedded Technology and Applications Symposium.

[16]  Luca Benini,et al.  Real-time scheduling for energy harvesting sensor nodes , 2007, Real-Time Systems.

[17]  Rajesh K. Gupta,et al.  Energy-aware task scheduling with task synchronization for embedded real-time systems , 2002, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[18]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks: the single-node case , 1993, TNET.

[19]  Weixun Wang,et al.  TCEC: Temperature and Energy-Constrained Scheduling in Real-Time Multitasking Systems , 2012, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[20]  Luca P. Carloni,et al.  Proceedings of the tenth ACM international conference on Embedded software , 2010 .

[21]  Rami G. Melhem,et al.  Maximizing the system value while satisfying time and energy constraints , 2003, IBM J. Res. Dev..