TY - GEN
T1 - AppFlow
T2 - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010
AU - Khargharia, Bithika
AU - Luo, Haoting
AU - Al-Nashif, Youssif
AU - Hariri, Salim
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - The characteristic of dramatic fluctuation in the resource provisioning for real-time applications calls for an elastic delivery of computing services. Current datacenter deployment schemes, which feature a strong tie between servers and applications, are increasingly challenged to ensure power efficiency in terms of multiple peak loads provisioning, optimal average resources utilization, variable runtime workloads profiling, datacenter manageability and overhead control on the datacenter Total Cost of Ownership (TCO). Researchers have exploited paradigms such as virtualization and migration for large-scale computing systems; however, there is still a long way before we can optimally address the power-performance trade-off. This paper provides an autonomic power management scheme for the resource provisioning process for large-scale data centers while meeting the Service-Level Agreement (SLA) and power requirements. The system status is continuously monitored using a cross-layered hierarchy to optimally scale up and down the virtual machine resources such that power and performance can be optimized. We have applied our technique to autonomically manage high performance platforms with multi-core processors and multi rank memory subsystems. Our experimental results show around 56.25% platform energy savings for memory-intensive workload, 63.75% platform energy savings for processor-intensive workload and 47.5% platform energy savings for mixed workload while maintaining.
AB - The characteristic of dramatic fluctuation in the resource provisioning for real-time applications calls for an elastic delivery of computing services. Current datacenter deployment schemes, which feature a strong tie between servers and applications, are increasingly challenged to ensure power efficiency in terms of multiple peak loads provisioning, optimal average resources utilization, variable runtime workloads profiling, datacenter manageability and overhead control on the datacenter Total Cost of Ownership (TCO). Researchers have exploited paradigms such as virtualization and migration for large-scale computing systems; however, there is still a long way before we can optimally address the power-performance trade-off. This paper provides an autonomic power management scheme for the resource provisioning process for large-scale data centers while meeting the Service-Level Agreement (SLA) and power requirements. The system status is continuously monitored using a cross-layered hierarchy to optimally scale up and down the virtual machine resources such that power and performance can be optimized. We have applied our technique to autonomically manage high performance platforms with multi-core processors and multi rank memory subsystems. Our experimental results show around 56.25% platform energy savings for memory-intensive workload, 63.75% platform energy savings for processor-intensive workload and 47.5% platform energy savings for mixed workload while maintaining.
KW - Autonomic computing
KW - Data center
KW - Power management
UR - http://www.scopus.com/inward/record.url?scp=79953113774&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79953113774&partnerID=8YFLogxK
U2 - 10.1109/GreenCom-CPSCom.2010.103
DO - 10.1109/GreenCom-CPSCom.2010.103
M3 - Conference contribution
AN - SCOPUS:79953113774
SN - 9780769543314
T3 - Proceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010
SP - 103
EP - 111
BT - Proceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010
Y2 - 18 December 2010 through 20 December 2010
ER -