A fast parametric maximum flow algorithm and applications
SIAM Journal on Computing
Optimal voltage allocation techniques for dynamically variable voltage processors
Proceedings of the 40th annual Design Automation Conference
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
On energy-optimal voltage scheduling for fixed-priority hard real-time systems
ACM Transactions on Embedded Computing Systems (TECS)
Approximation Algorithms for Scheduling Multiple Feasible Interval Jobs
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
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)
Energy efficient online deadline scheduling
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Scheduling for Speed Bounded Processors
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
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In this paper, we study the scheduling problem of jobs with multiple active intervals. Each job in the problem instance has n(n=1) disjoint active time intervals where it can be executed and a workload characterized by the required number of CPU cycles. Previously, people studied multiple interval job scheduling problem where each job must be assigned enough CPU cycles in one of its active intervals. We study a different practical version where the partial work done by the end of an interval remains valid and each job is considered finished if total CPU cycles assigned to it in all its active intervals reach the requirement. The goal is to find a feasible schedule that minimizes energy consumption. By adapting the algorithm for single interval jobs proposed in Yao, Demers and Shenker (1995) [1], one can still obtain an optimal schedule. However, the two phases in that algorithm (critical interval finding and scheduling the critical interval) can no longer be carried out directly. We present polynomial time algorithms to solve the two phases for jobs with multiple active intervals and therefore can still compute the optimal schedule in polynomial time.