TY - GEN
T1 - DVS Scheduling in a Line or a Star Network of Processors
AU - Mu, Zongxu
AU - Li, Minming
PY - 2013/6
Y1 - 2013/6
N2 - Dynamic Voltage Scaling (DVS) is a technique which allows the processors to change speed when executing jobs. Most of the previous works either study single processor or multiple parallel processors. In this paper, we consider a network of DVS enabled processors. Every job needs to go along a certain path in the network and has a certain workload finished on any processor it goes through before it moves on to the next processor. Our objective is to minimize the total energy consumption while finishing every job before its deadline. Due to the intrinsic complexity of this problem, we only focus on line networks with two nodes and a simple one-level tree network (a star). We show that in some of these simple cases, the optimal schedule can be computed efficiently and interleaving is not needed to achieve optimality. However, in both types of networks, how to find the optimal sequence of execution remains a big challenge for jobs with general workloads.
AB - Dynamic Voltage Scaling (DVS) is a technique which allows the processors to change speed when executing jobs. Most of the previous works either study single processor or multiple parallel processors. In this paper, we consider a network of DVS enabled processors. Every job needs to go along a certain path in the network and has a certain workload finished on any processor it goes through before it moves on to the next processor. Our objective is to minimize the total energy consumption while finishing every job before its deadline. Due to the intrinsic complexity of this problem, we only focus on line networks with two nodes and a simple one-level tree network (a star). We show that in some of these simple cases, the optimal schedule can be computed efficiently and interleaving is not needed to achieve optimality. However, in both types of networks, how to find the optimal sequence of execution remains a big challenge for jobs with general workloads.
UR - http://www.scopus.com/inward/record.url?scp=84884946935&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84884946935&origin=recordpage
U2 - 10.1007/978-3-642-38768-5_11
DO - 10.1007/978-3-642-38768-5_11
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783642387678
T3 - Lecture Notes in Computer Science
SP - 101
EP - 113
BT - Computing and Combinatorics
A2 - Du, Ding-Zhu
A2 - Zhang, Guochuan
PB - Springer Verlag
T2 - 19th International Computing and Combinatorics Conference (COCOON 2013)
Y2 - 21 June 2013 through 21 June 2013
ER -