Autonomic Performance and Power Control for Co-Located Web Applications in Virtualized Datacenters

In a datacenter, complex and time-varying interactions between various tiers and services of web applications, and the contention of shared resources among co-located virtual machines have significant impact on the user perceived performance and power consumption of the underlying system. We propose and develop APPLEware, an autonomic middleware for joint performance and power control of co-located web applications in virtualized datacenters. It features a distributed control structure that provides predictable performance and energy efficiency for large complex systems. It applies machine learning based self-adaptive modeling to capture the complex and time-varying relationship between the application performance and allocation of resources to various application components, in the face of highly dynamic and bursty workloads. The distributed controllers coordinate with each other and allocate resources to meet the service level agreements of applications in an agile and energy-efficient manner. Experimental results based on a testbed implementation with benchmark applications and large scale simulations demonstrate APPLEware's effectiveness, energy efficiency and scalability.

[1]  Yinyu Ye,et al.  Interior point algorithms: theory and analysis , 1997 .

[2]  Evgenia Smirni,et al.  Injecting realistic burstiness to a traditional client-server benchmark , 2009, ICAC '09.

[3]  Xiaobo Zhou,et al.  Coordinated Power and Performance Guarantee with Fuzzy MIMO Control in Virtualized Server Clusters , 2015, IEEE Transactions on Computers.

[4]  Michael D. Smith,et al.  Improving Performance Isolation on Chip Multiprocessors via an Operating System Scheduler , 2007, 16th International Conference on Parallel Architecture and Compilation Techniques (PACT 2007).

[5]  Xue Liu,et al.  Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay Control , 2007, IEEE Transactions on Computers.

[6]  Calton Pu,et al.  Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures , 2010, 2010 IEEE 30th International Conference on Distributed Computing Systems.

[7]  Jordi Torres,et al.  GreenHadoop: leveraging green energy in data-processing frameworks , 2012, EuroSys '12.

[8]  Prashant J. Shenoy,et al.  Agile dynamic provisioning of multi-tier Internet applications , 2008, TAAS.

[9]  Mark S. Squillante,et al.  A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms , 2013, IEEE Transactions on Dependable and Secure Computing.

[10]  Cheng-Zhong Xu,et al.  vPnP: Automated coordination of power and performance in virtualized datacenters , 2010, 2010 IEEE 18th International Workshop on Quality of Service (IWQoS).

[11]  Gargi Dasgupta,et al.  BrownMap: Enforcing Power Budget in Shared Data Centers , 2010, Middleware.

[12]  Zhenhuan Gong,et al.  PAC: Pattern-driven Application Consolidation for Efficient Cloud Computing , 2010, 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.

[13]  Amin Vahdat,et al.  Enforcing Performance Isolation Across Virtual Machines in Xen , 2006, Middleware.

[14]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[15]  Xiaohui Gu,et al.  CloudScale: elastic resource scaling for multi-tenant cloud systems , 2011, SoCC.

[16]  János Abonyi,et al.  Effective optimization for fuzzy model predictive control , 2004, IEEE Transactions on Fuzzy Systems.

[17]  Manish Marwah,et al.  Probabilistic performance modeling of virtualized resource allocation , 2010, ICAC '10.

[18]  Xiaobo Zhou,et al.  Autonomic performance and power control for co-located Web applications on virtualized servers , 2013, 2013 IEEE/ACM 21st International Symposium on Quality of Service (IWQoS).

[19]  Adam Wierman,et al.  Renewable and cooling aware workload management for sustainable data centers , 2012, SIGMETRICS '12.

[20]  Thu D. Nguyen,et al.  Reducing electricity cost through virtual machine placement in high performance computing clouds , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[21]  Jerome A. Rolia,et al.  Resource and virtualization costs up in the cloud: Models and design choices , 2011, 2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN).

[22]  Yefu Wang,et al.  Coordinating Power Control and Performance Management for Virtualized Server Clusters , 2011, IEEE Transactions on Parallel and Distributed Systems.

[23]  Martin Arlitt,et al.  A workload characterization study of the 1998 World Cup Web site , 2000, IEEE Netw..

[24]  Daniel Mossé,et al.  Stochastic approximation control of power and tardiness in a three-tier web-hosting cluster , 2010, ICAC '10.

[25]  Xiao Zhang,et al.  CPI2: CPU performance isolation for shared compute clusters , 2013, EuroSys '13.

[26]  Xiaobo Zhou,et al.  NINEPIN: Non-invasive and energy efficient performance isolation in virtualized servers , 2012, IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012).

[27]  Xiaorui Wang,et al.  SHIP: A Scalable Hierarchical Power Control Architecture for Large-Scale Data Centers , 2012, IEEE Transactions on Parallel and Distributed Systems.

[28]  Karsten Schwan,et al.  VirtualPower: coordinated power management in virtualized enterprise systems , 2007, SOSP.

[29]  Aman Kansal,et al.  Q-clouds: managing performance interference effects for QoS-aware clouds , 2010, EuroSys '10.

[30]  Manish Marwah,et al.  Minimizing data center SLA violations and power consumption via hybrid resource provisioning , 2011, 2011 International Green Computing Conference and Workshops.

[31]  Bruce H. Krogh,et al.  Distributed model predictive control , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[32]  Guillaume Pierre,et al.  Autonomous resource provisioning for multi-service web applications , 2010, WWW '10.

[33]  Alexandra Fedorova,et al.  Addressing shared resource contention in multicore processors via scheduling , 2010, ASPLOS XV.

[34]  Calton Pu,et al.  Performance and availability aware regeneration for cloud based multitier applications , 2010, 2010 IEEE/IFIP International Conference on Dependable Systems & Networks (DSN).

[35]  Xiao Zhang,et al.  Towards practical page coloring-based multicore cache management , 2009, EuroSys '09.

[36]  Quanyan Zhu,et al.  Dynamic energy-aware capacity provisioning for cloud computing environments , 2012, ICAC '12.

[37]  Martin Arlitt,et al.  Workload Characterization of the 1998 World Cup Web Site , 1999 .

[38]  Prashant J. Shenoy,et al.  Yank: Enabling Green Data Centers to Pull the Plug , 2013, NSDI.

[39]  Wei Lin,et al.  Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing , 2014, OSDI.

[40]  Jie Liu,et al.  Power Budgeting for Virtualized Data Centers , 2011, USENIX Annual Technical Conference.

[41]  Julie A. McCann,et al.  A survey of autonomic computing—degrees, models, and applications , 2008, CSUR.

[42]  Ravishankar K. Iyer,et al.  CloudVal: A framework for validation of virtualization environment in cloud infrastructure , 2011, 2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN).

[43]  Kang G. Shin,et al.  Automated control of multiple virtualized resources , 2009, EuroSys '09.