A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Algorithmic problems in power management
ACM SIGACT News
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
An Efficient Algorithm for Computing Optimal Discrete Voltage Schedules
SIAM Journal on Computing
Speed scaling to manage energy and temperature
Journal of the ACM (JACM)
ACM Transactions on Algorithms (TALG)
Queue - Power Management
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Optimal power allocation in server farms
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Improved Bounds for Speed Scaling in Devices Obeying the Cube-Root Rule
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Polynomial time algorithms for minimum energy scheduling
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Optimisation of Energy Consumption of Soft Real-Time Applications by Workload Prediction
ISORCW '10 Proceedings of the 2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops
Deadline scheduling and power management for speed bounded processors
Theoretical Computer Science
Algorithmica
Dimetrodon: processor-level preventive thermal management via idle cycle injection
Proceedings of the 48th Design Automation Conference
Slow down and sleep for profit in online deadline scheduling
MedAlg'12 Proceedings of the First Mediterranean conference on Design and Analysis of Algorithms
Computational sprinting on a hardware/software testbed
Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
Do language constructs for concurrent execution have impact on energy efficiency?
Proceedings of the 2013 companion publication for conference on Systems, programming, & applications: software for humanity
Online parallel scheduling of non-uniform tasks: trading failures for energy
FCT'13 Proceedings of the 19th international conference on Fundamentals of Computation Theory
Hi-index | 0.00 |
We study an energy conservation problem where a variable-speed processor is equipped with a sleep state. Executing jobs at high speeds and then setting the processor asleep is an approach that can lead to further energy savings compared to standard dynamic speed scaling. We consider classical deadline-based scheduling, i.e. each job is specified by a release time, a deadline and a processing volume. For general convex power functions, Irani et al. [12] devised an offline 2-approximation algorithm. Roughly speaking, the algorithm schedules jobs at a critical speed Scrit that yields the smallest energy consumption while jobs are processed. For power functions P(s) = sα + γ, where s is the processor speed, Han et al. [11] gave an (αα + 2)-competitive online algorithm. We investigate the offline setting of speed scaling with a sleep state. First we prove NP-hardness of the optimization problem. Additionally, we develop lower bounds, for general convex power functions: No algorithm that constructs Scrit-schedules, which execute jobs at speeds of at least scrit, can achieve an approximation factor smaller than 2. Furthermore, no algorithm that minimizes the energy expended for processing jobs can attain an approximation ratio smaller than 2. We then present an algorithmic framework for designing good approximation algorithms. For general convex power functions, we derive an approximation factor of 4/3. For power functions P(s) = βsα + γ, we obtain an approximation of 137/117 Scrit-schedules. For general convex power functions, we give another 2-approximation algorithm. For functions P(s) = βsα + γ, we present tight upper and lower bounds on the best possible approximation factor. The ratio is exactly eW−1(−e−1−1/e)/(eW−1(−e−1−1/e) + 1) W function.