Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Multi-processor scheduling to minimize flow time with ε resource augmentation
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Approximating total flow time on parallel machines
Journal of Computer and System Sciences
ACM Transactions on Algorithms (TALG)
Energy-efficient algorithms for flow time minimization
ACM Transactions on Algorithms (TALG)
SRPT optimally utilizes faster machines to minimize flow time
ACM Transactions on Algorithms (TALG)
Scalably scheduling processes with arbitrary speedup curves
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Proceedings of the forty-first annual ACM symposium on Theory of computing
Sleep with Guilt and Work Faster to Minimize Flow Plus Energy
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Communications of the ACM
Optimality analysis of energy-performance trade-off for server farm management
Performance Evaluation
Energy efficient scheduling via partial shutdown
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Scalably scheduling power-heterogeneous processors
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Non-clairvoyant speed scaling for weighted flow time
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Sleep management on multiple machines for energy and flow time
ICALP'11 Proceedings of the 38th international colloquim conference on Automata, languages and programming - Volume Part I
Scheduling heterogeneous processors isn't as easy as you think
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Generalized machine activation problems
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Online scheduling on identical machines using SRPT
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
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In large data centers, managing the availability of servers is often non-trivial, especially when the workload is unpredictable. Using too many servers would waste energy, while using too few would affect the performance. A recent theoretical study, which assumes the clairvoyant model where job size is known at arrival time, has successfully integrated sleep-and-wakeup management into multi-processor job scheduling and obtained a competitive tradeoff between flow time and energy [6]. This paper extends the study to the nonclairvoyant model where the size of a job is not known until the job is finished. We give a new online algorithm SATA which is, for any ε 0, (1 + ε)-speed O( 1⁄ε2 )-competitive for the objective of minimizing the sum of flow time and energy. SATA also gives a new nonclairvoyant result for the classic setting where all processors are always on and the concern is flow time only. In this case, the previous work of Chekuri et al. [7] and Chadha et al. [8] has revealed that random dispatching can give a non-migratory algorithm that is (1 + ε)-speed O( 1⁄ε3 )-competitive, and any deterministic non-migratory algorithm is Ω(m⁄s)-competitive using s-speed processors [7], where m is the number of processors. SATA, which is a deterministic algorithm migrating each job at most four times on average, has a competitive ratio of O(1⁄ε2). The number of migrations used by SATA is optimal up to a constant factor as we can extend the above lower bound result.