TY - GEN
T1 - Energy-efficient scheduling with time and processors eligibility restrictions
AU - Jin, Xibo
AU - Zhang, Fa
AU - Song, Ying
AU - Fan, Liya
AU - Liu, Zhiyong
PY - 2013
Y1 - 2013
N2 - While previous work on energy-efficient algorithms focused on assumption that tasks can be assigned to any processor, we initially study the problem of task scheduling on restricted parallel processors. The objective is to minimize the overall energy consumption while speed scaling (SS) method is used to reduce energy consumption under the execution time constraint (Makespan C max). In this work, we discuss the speed setting in the continuous model that processors can run at arbitrary speed in [smin,s max]. The energy-efficient scheduling problem, involving task assignment and speed scaling, is inherently complicated as it is proved to be NP-Complete. We formulate the problem as an Integer Programming (IP) problem. Specifically, we devise a polynomial time optimal scheduling algorithm for the case tasks have an uniform size. Our algorithm runs in O(mn3 logn) time, where m is the number of processors and n is the number of tasks. We then present a polynomial time algorithm that achieves an approximation factor of 2α-1 (2-1/mα) (α is the power parameter) when the tasks have arbitrary size work.
AB - While previous work on energy-efficient algorithms focused on assumption that tasks can be assigned to any processor, we initially study the problem of task scheduling on restricted parallel processors. The objective is to minimize the overall energy consumption while speed scaling (SS) method is used to reduce energy consumption under the execution time constraint (Makespan C max). In this work, we discuss the speed setting in the continuous model that processors can run at arbitrary speed in [smin,s max]. The energy-efficient scheduling problem, involving task assignment and speed scaling, is inherently complicated as it is proved to be NP-Complete. We formulate the problem as an Integer Programming (IP) problem. Specifically, we devise a polynomial time optimal scheduling algorithm for the case tasks have an uniform size. Our algorithm runs in O(mn3 logn) time, where m is the number of processors and n is the number of tasks. We then present a polynomial time algorithm that achieves an approximation factor of 2α-1 (2-1/mα) (α is the power parameter) when the tasks have arbitrary size work.
UR - http://www.scopus.com/inward/record.url?scp=84883204927&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40047-6_10
DO - 10.1007/978-3-642-40047-6_10
M3 - Conference contribution
AN - SCOPUS:84883204927
SN - 9783642400469
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 66
EP - 77
BT - Euro-Par 2013 Parallel Processing - 19th International Conference, Proceedings
T2 - 19th International Conference on Parallel Processing, Euro-Par 2013
Y2 - 26 August 2013 through 30 August 2013
ER -