TY - JOUR
T1 - Dynamic resource management in energy constrained heterogeneous computing systems using voltage scaling
AU - Kim, Jong Kook
AU - Siegel, Howard Jay
AU - Maciejewski, Anthony A.
AU - Eigenmann, Rudolf
N1 - Funding Information:
The authors thank Sameer Shivle, Prasanna Sugavanam, and T.N. Vijaykumar for their valuable comments. A preliminary version of portions of this material was presented at the 19th International Parallel and Distributed Processing Symposium. This research was supported by the US National Science Foundation under Grant CNS-0615170, the Colorado State University George T. Abell Endowment, and the Korea University Grant. Submitted to the IEEE TPDS Special Section on Power-Aware Parallel and Distributed Systems in October 2007.
PY - 2008
Y1 - 2008
N2 - An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.
AB - An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.
KW - Ad hoc
KW - Distributed heterogeneous computing
KW - Dynamic resource allocation/management
KW - Dynamic voltage scaling
KW - Energy-aware computing
KW - Task priorities and deadlines
UR - http://www.scopus.com/inward/record.url?scp=54249165363&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=54249165363&partnerID=8YFLogxK
U2 - 10.1109/TPDS.2008.113
DO - 10.1109/TPDS.2008.113
M3 - Article
AN - SCOPUS:54249165363
VL - 19
SP - 1445
EP - 1457
JO - IEEE Transactions on Parallel and Distributed Systems
JF - IEEE Transactions on Parallel and Distributed Systems
SN - 1045-9219
IS - 11
ER -