ISCA '94 Proceedings of the 21st annual international symposium on Computer architecture
ICS '90 Proceedings of the 4th international conference on Supercomputing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
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SIAM Journal on Computing
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SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Convex programming for scheduling unrelated parallel machines
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
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)
Approximation Algorithms for the Job Interval Selection Problem and Related Scheduling Problems
Mathematics of Operations Research
Resource Minimization Job Scheduling
APPROX '09 / RANDOM '09 Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
Communications of the ACM
Power-saving scheduling for weakly dynamic voltage scaling devices
WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
On the value of preemption in scheduling
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We consider the following offline variant of the speed scaling problem introduced by Yao et al. We are given a set of jobs and we have a variable-speed processor to process them. The higher the processor speed, the higher the energy consumption. Each job is associated with its own release time, deadline, and processing volume. The objective is to find a feasible schedule that minimizes the energy consumption. In contrast to Yao et al., no preemption of jobs is allowed. Unlike the preemptive version that is known to be in P, the non-preemptive version of speed scaling is strongly NP-hard. In this work, we present a constant factor approximation algorithm for it. The main technical idea is to transform the problem into the unrelated machine scheduling problem with $$L_p$$ -norm objective.