Energy efficient operating systems and software

• Main Author: Sinha, Amit, 1976-
• Other Authors: Anantha Chandrakasan.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2014
• Subjects: Electrical Engineering and Computer Science.
• Online Access: http://hdl.handle.net/1721.1/86773

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001. === Includes bibliographical references (p. 153-159). === Energy efficient system design is becoming increasingly important with the proliferation of portable, battery-operated appliances such as laptops, Personal Digital Assistants (PDAs) and cellular phones. Numerous dedicated hardware approaches for energy mini-mization have been proposed while software energy efficiency has been relatively unexplored. Since it is the software that drives the hardware, decisions taken during software design can have a significant impact on system energy consumption. This thesis explores avenues for improving system energy efficiency from application level to the operating system level. The embedded operating system can have a significant impact on system energy by performing dynamic power management both in the active and passive states of the device. Software controlled active power management techniques using dynamic voltage and frequency scaling have been explored. Efficient workload prediction strategies have been developed that enable just-in-time computation. An algorithm for efficient real-time operating system task scheduling has also been developed that minimizes energy consumption. Portable systems spend a lot of time in sleep mode. Idle power management strategies have been developed that consider the effect of leakage and duty-cycle on system lifetime. A hierarchical shutdown approach for systems characterized multiple sleep states has been proposed. Although the proposed techniques are quite general, their applicability and utility have been demonstrated using the MIT [mu]AMPS wireless sensor node an example system wherever possible. === (cont.) To quantify software energy consumption, an estimation framework has been developed based on experiments on the StrongARM and Hitachi processors. The software energy profiling tool is available on-line. Finally, in energy constrained systems, we would like to have the ability to trade-off quality of service for extended battery life. A scalable approach to application development has been demonstrated that allows energy quality trade-offs. === by Amit Sinha. === Ph.D.