2002 · 382 citations · 39 references
EngineeringEnergy EfficiencyComputer ArchitectureEnergy AccountingSystems EngineeringPower-aware DesignPower-aware SoftwareCurrentcy ModelPower ManagementEnergy ConsumptionPower-aware ComputingComputer EngineeringMobile ComputingComputer ScienceOperating SystemsEnergy ManagementEdge ComputingPower-efficient ComputingSystem Software
Energy consumption is a major challenge in computer systems design, and its global nature introduces complexities beyond conventional resource management. The study proposes the Currentcy Model to treat energy as a first‑class OS resource, aiming to extend battery life by limiting average discharge and fairly allocating energy among tasks per user preferences. The authors implemented ECOSystem, a Linux variant incorporating the Currentcy Model, to provide explicit battery‑resource control across diverse hardware. Experimental results show that ECOSystem accurately accounts for energy consumed by asynchronous device operation, achieves a target battery lifetime, and proportionally shares the limited energy resource among competing tasks.
Energy consumption has recently been widely recognized as a major challenge of computer systems design. This paper explores how to support energy as a first-class operating system resource. Energy, because of its global system nature, presents challenges beyond those of conventional resource management. To meet these challenges we propose the Currentcy Model that unifies energy accounting over diverse hardware components and enables fair allocation of available energy among applications. Our particular goal is to extend battery lifetime by limiting the average discharge rate and to share this limited resource among competing task according to user preferences. To demonstrate how our framework supports explicit control over the battery resource we implemented ECOSystem, a modified Linux, that incorporates our currentcy model. Experimental results show that ECOSystem accurately accounts for the energy consumed by asynchronous device operation, can achieve a target battery lifetime, and proportionally shares the limited energy resource among competing tasks.
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Proceedings of the 24th international conference on Machine learning
2007 · 11.7K citations
A scheduling model for reduced CPU energy
Fei Yao, Alan Demers, Scott Shenker · 2002 · 1.5K citations
Mathematical Programming, Engineering, Energy Efficiency +19