TY - GEN
T1 - Energy-aware job management approaches for workflow in cloud
AU - Khaleel, Mustafa
AU - Zhu, Michelle M.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/26
Y1 - 2015/10/26
N2 - The energy consumption of cloud servers has dramatically increased. In order to meet the growing demands of users and reduce the skyrocketing cost of electricity, it is critical to have performance guaranteed and cost-effective job schedulers for clouds. In recent years, there has been a growing body of research which focus on improving resource utilization to improve energy efficiency, system throughput and at the same time meet the Quality of Service (QoS) requirements specified in the Service Level Agreements (SLA). This paper propose a multiple procedure scheduling algorithm which aims to maximize the resource utilization for cloud resources for reduced energy consumption as well as guarantee the execution deadline for cloud jobs modeled as scientific workflows. Our simulation results demonstrate better performance compared with other similar algorithms.
AB - The energy consumption of cloud servers has dramatically increased. In order to meet the growing demands of users and reduce the skyrocketing cost of electricity, it is critical to have performance guaranteed and cost-effective job schedulers for clouds. In recent years, there has been a growing body of research which focus on improving resource utilization to improve energy efficiency, system throughput and at the same time meet the Quality of Service (QoS) requirements specified in the Service Level Agreements (SLA). This paper propose a multiple procedure scheduling algorithm which aims to maximize the resource utilization for cloud resources for reduced energy consumption as well as guarantee the execution deadline for cloud jobs modeled as scientific workflows. Our simulation results demonstrate better performance compared with other similar algorithms.
KW - Energy-aware
KW - Scientific workflow scheduling
KW - Task consolidation
UR - http://www.scopus.com/inward/record.url?scp=84959311497&partnerID=8YFLogxK
U2 - 10.1109/CLUSTER.2015.85
DO - 10.1109/CLUSTER.2015.85
M3 - Conference contribution
AN - SCOPUS:84959311497
T3 - Proceedings - IEEE International Conference on Cluster Computing, ICCC
SP - 506
EP - 507
BT - Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Cluster Computing, CLUSTER 2015
Y2 - 8 September 2015 through 11 September 2015
ER -