Access the full text.
Sign up today, get DeepDyve free for 14 days.
ACM Transactions on Autonomous and Adaptive Systems
Zhenhuan Gong, Xiaohui Gu (2010)
PAC: Pattern-driven Application Consolidation for Efficient Cloud Computing2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Akshat Verma, Puneet Ahuja, A. Neogi (2008)
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems
Xiaorui Wang, Yefu Wang (2009)
Co-Con: Coordinated control of power and application performance for virtualized server clusters2009 17th International Workshop on Quality of Service
Anshul Gandhi, Mor Harchol-Balter, R. Das, C. Lefurgy (2009)
Optimal power allocation in server farms
C. Lefurgy, Xiaorui Wang, Malcolm Allen-Ware (2007)
Server-Level Power ControlFourth International Conference on Autonomic Computing (ICAC'07)
Haichuan Wang, Qiming Teng, Xiao Zhong, P. Sweeney (2010)
Using the middle tier to understand cross-tier delay in a multi-tier application2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
Y. Diao, J. Hellerstein, S. Parekh, Hidayatullah Shaikh, M. Surendra (2006)
Controlling Quality of Service in Multi-Tier Web Applications26th IEEE International Conference on Distributed Computing Systems (ICDCS'06)
Qingyang Wang, Yasuhiko Kanemasa, Jack Li, Chien-An Lai, Masazumi Matsubara, C. Pu (2013)
Impact of DVFS on n-tier application performanceProceedings of the First ACM SIGOPS Conference on Timely Results in Operating Systems
Xiaorui Wang, Ming Chen, C. Lefurgy, Tom Keller (2010)
SHIP: A Scalable Hierarchical Power Control Architecture for Large-Scale Data Centers — Supplementary File
P. Lama, Xiaobo Zhou (2012)
NINEPIN: Non-invasive and energy efficient performance isolation in virtualized serversIEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012)
Hua Wang, Kazuo Tanaka, M. Griffin (1996)
An approach to fuzzy control of nonlinear systems: stability and design issuesIEEE Trans. Fuzzy Syst., 4
P. Lama, Xiaobo Zhou (2013)
Autonomic Provisioning with Self-Adaptive Neural Fuzzy Control for Percentile-Based Delay GuaranteeACM Trans. Auton. Adapt. Syst., 8
Yuehui Chen, Bo-Seok Yang, A. Abraham, Lizhi Peng (2007)
Automatic Design of Hierarchical Takagi–Sugeno Type Fuzzy Systems Using Evolutionary AlgorithmsIEEE Transactions on Fuzzy Systems, 15
Anshul Gandhi, Mor Harchol-Balter, M. Kozuch (2011)
The case for sleep states in servers
Yanfei Guo, P. Lama, Xiaobo Zhou (2012)
Automated and Agile Server Parameter Tuning with Learning and Control2012 IEEE 26th International Parallel and Distributed Processing Symposium
P. Lama, Yanfei Guo, Xiaobo Zhou (2013)
Autonomic performance and power control for co-located Web applications on virtualized servers2013 IEEE/ACM 21st International Symposium on Quality of Service (IWQoS)
Mootaz Elnozahy, M. Kistler, R. Rajamony (2003)
Energy Conservation Policies for Web Servers
Christopher Stewart, T. Kelly, A. Zhang (2007)
Exploiting nonstationarity for performance prediction
Dazhao Cheng, Yanfei Guo, Xiaobo Zhou (2013)
Self-Tuning Batching with DVFS for Improving Performance and Energy Efficiency in Servers2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems
D. Hagimont, Christine Kamga, L. Broto, A. Tchana, N. Palma (2013)
DVFS Aware CPU Credit Enforcement in a Virtualized System
Xiaorui Wang, Ming Chen, Xing Fu (2010)
MIMO Power Control for High-Density Servers in an EnclosureIEEE Transactions on Parallel and Distributed Systems, 21
Gueyoung Jung, M. Hiltunen, Kaustubh Joshi, R. Schlichting, C. Pu (2010)
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures2010 IEEE 30th International Conference on Distributed Computing Systems
Yanfei Guo, P. Lama, J. Rao, Xiaobo Zhou (2013)
V-Cache: Towards Flexible Resource Provisioning for Multi-tier Applications in IaaS Clouds2013 IEEE 27th International Symposium on Parallel and Distributed Processing
V. Sharma, Arun Thomas, T. Abdelzaher, K. Skadron, Zhijian Lu (2003)
Power-aware QoS management in Web serversRTSS 2003. 24th IEEE Real-Time Systems Symposium, 2003
Sanjay Kumar, V. Talwar, Vibhore Kumar, Parthasarathy Ranganathan, K. Schwan (2009)
vManage: loosely coupled platform and virtualization management in data centers
Pradeep Padala, Kai-yuan Hou, K. Shin, Xiaoyun Zhu, Mustafa Uysal, Zhikui Wang, S. Singhal, A. Merchant (2009)
Automated control of multiple virtualized resources
B. Urgaonkar, Prashant Shenoy, A. Chandra, P. Goyal, Timothy Wood (2008)
Agile dynamic provisioning of multi-tier Internet applicationsACM Trans. Auton. Adapt. Syst., 3
O. Unsal, I. Koren (2003)
System-level power-aware design techniques in real-time systemsProc. IEEE, 91
P. Lama, Xiaobo Zhou (2011)
PERFUME: Power and performance guarantee with fuzzy MIMO control in virtualized servers2011 IEEE Nineteenth IEEE International Workshop on Quality of Service
Jiayu Gong, Chengzhong Xu (2010)
vPnP: Automated coordination of power and performance in virtualized datacenters2010 IEEE 18th International Workshop on Quality of Service (IWQoS)
B. Addis, D. Ardagna, B. Panicucci, M. Squillante, Li Zhang (2013)
A Hierarchical Approach for the Resource Management of Very Large Cloud PlatformsIEEE Transactions on Dependable and Secure Computing, 10
Anshul Gandhi, Yuan Chen, D. Gmach, M. Arlitt, M. Marwah (2011)
Minimizing data center SLA violations and power consumption via hybrid resource provisioning2011 International Green Computing Conference and Workshops
Yefu Wang, Xiaorui Wang (2013)
Virtual Batching: Request Batching for Server Energy Conservation in Virtualized Data CentersIEEE Transactions on Parallel and Distributed Systems, 24
T. Horvath, T. Abdelzaher, K. Skadron, Xue Liu (2007)
Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay ControlIEEE Transactions on Computers, 56
Ripal Nathuji, C. Isci, E. Gorbatov (2007)
Exploiting Platform Heterogeneity for Power Efficient Data CentersFourth International Conference on Autonomic Computing (ICAC'07)
Self-Tuning Batching with DVFS for Performance Improvement and Energy Efficiency in Internet Servers DAZHAO CHENG and YANFEI GUO, University of Colorado, Colorado Springs CHANGJUN JIANG, Tongji University, China XIAOBO ZHOU, University of Colorado, Colorado Springs Performance improvement and energy efficiency are two important goals in provisioning Internet services in datacenter servers. In this article, we propose and develop a self-tuning request batching mechanism to simultaneously achieve the two correlated goals. The batching mechanism increases the cache hit rate at the front-tier Web server, which provides the opportunity to improve an application's performance and the energy efficiency of the server system. The core of the batching mechanism is a novel and practical two-layer control system that adaptively adjusts the batching interval and frequency states of CPUs according to the service level agreement and the workload characteristics. The batching control adopts a self-tuning fuzzy model predictive control approach for application performance improvement. The power control dynamically adjusts the frequency of Central Processing Units (CPUs) with Dynamic Voltage and Frequency Scaling (DVFS) in response to workload fluctuations for energy efficiency. A coordinator between the two control loops achieves the desired performance and energy efficiency. We further extend the self-tuning batching with
ACM Transactions on Autonomous and Adaptive Systems (TAAS) – Association for Computing Machinery
Published: Mar 25, 2015
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.