Hammerstein-Wiener nonlinear model based predictive control for relative QoS performance and resource management of software systems

Abstract Runtime management of Quality of Service (QoS) performance and resource provisioning is a vital issue in shared resource software environments. A useful performance management technique for such software systems is the relative guarantee feedback control scheme. The existing approaches for this class of control systems are mainly based on off-line linear or on-line model identification and control techniques, which tend to have performance issues in the presence of nonlinearities induced by this scheme. Instead of using such modeling techniques, this paper proposes a new approach for QoS performance management and resource provisioning by using an off-line identification of Hammerstein and Wiener nonlinear block structural model. Using the characteristic structure of the nonlinear model, a predictive feedback controller based on a gain schedule technique is incorporated in the design to achieve the performance objectives. The proposed approach is validated using experiments based on a prototype, demonstrating superior runtime QoS performance management and resource provisioning in a complex software system.

[1]  Francisco Jurado,et al.  Hammerstein‐model‐based predictive control of micro‐turbines , 2006 .

[2]  Alberto Bemporad,et al.  Robust model predictive control: A survey , 1998, Robustness in Identification and Control.

[3]  Sang Hyuk Son,et al.  A feedback control approach for guaranteeing relative delays in Web servers , 2001, Proceedings Seventh IEEE Real-Time Technology and Applications Symposium.

[4]  Su Whan Sung,et al.  Improved system identification method for Hammerstein-Wiener processes , 2008 .

[5]  Nagarajan Kandasamy,et al.  Risk-Aware Limited Lookahead Control for Dynamic Resource Provisioning in Enterprise Computing Systems , 2006 .

[6]  S. Gerksic,et al.  Adaptive implementation of Wiener model based nonlinear predictive control , 1999, ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465).

[7]  Jun Han,et al.  A multi-model framework to implement self-managing control systems for QoS management , 2011, SEAMS '11.

[8]  Sang Hyuk Son,et al.  Feedback Control Architecture and Design Methodology for Service Delay Guarantees in Web Servers , 2006, IEEE Transactions on Parallel and Distributed Systems.

[9]  Sayed A. Banawan,et al.  An adaptive threshold based scheduling policy for ATM networks , 1996, Conference Proceedings of the 1996 IEEE Fifteenth Annual International Phoenix Conference on Computers and Communications.

[10]  W. R. Cluett,et al.  Identification of Wiener-type nonlinear systems in a noisy environment , 1997 .

[11]  Ing-Ray Chen,et al.  Threshold-based dynamic admission control algorithms for real-time multimedia servers , 1996, SAC '96.

[12]  Liuping Wang,et al.  From Plant Data to Process Control: Ideas for Process Identification and PID Design , 2000 .

[13]  F. M'Sahli,et al.  Nonlinear Model-Based Predictive Control Using a Generalised Hammerstein Model and its Application to a Semi-Batch Reactor , 2002 .

[14]  Dejun Mu,et al.  Feedback Control-Based QoS Guarantees in Web Application Servers , 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

[15]  J. Voros AN ITERATIVE METHOD FOR HAMMERSTEIN-WIENER SYSTEMS PARAMETER IDENTIFICATION , 2004 .

[16]  H. Rhee,et al.  Nonlinear Model Predictive Control Using a Wiener Model of a Continuous Methyl Methacrylate Polymerization Reactor , 2001 .

[17]  Lui Sha,et al.  Feedback control with queueing-theoretic prediction for relative delay guarantees in web servers , 2003, The 9th IEEE Real-Time and Embedded Technology and Applications Symposium, 2003. Proceedings..

[18]  Ladan Tahvildari,et al.  Self-adaptive software: Landscape and research challenges , 2009, TAAS.

[19]  Chenyang Lu,et al.  An adaptive control framework for QoS guarantees and its application to differentiated caching , 2002, IEEE 2002 Tenth IEEE International Workshop on Quality of Service (Cat. No.02EX564).

[20]  Xiaoyun Zhu,et al.  Utilization and SLO-Based Control for Dynamic Sizing of Resource Partitions , 2005, DSOM.

[21]  Xiaoyun Zhu,et al.  Utility-driven workload management using nested control design , 2006, 2006 American Control Conference.

[22]  R. Pearson,et al.  Gray-box identification of block-oriented nonlinear models , 2000 .

[23]  Liuping Wang,et al.  Model Predictive Control System Design and Implementation Using MATLAB , 2009 .

[24]  Ahmet Palazoglu,et al.  Model predictive control based on Wiener models , 1998 .

[25]  Chenyang Lu,et al.  ControlWare: a middleware architecture for feedback control of software performance , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[26]  W. R. Cluett,et al.  A new approach to the identification of pH processes based on the Wiener model , 1995 .

[27]  Xiaoyun Zhu,et al.  Triage: Performance differentiation for storage systems using adaptive control , 2005, TOS.

[28]  Waheed Iqbal,et al.  SLA-Driven Adaptive Resource Management for Web Applications on a Heterogeneous Compute Cloud , 2009, CloudCom.

[29]  S. Norquay,et al.  Application of Wiener model predictive control (WMPC) to an industrial C2-splitter , 1999 .

[30]  Drago Matko,et al.  Wiener model based nonlinear predictive control , 2000, Int. J. Syst. Sci..

[31]  Huan Liu,et al.  Web Server Farm in the Cloud: Performance Evaluation and Dynamic Architecture , 2009, CloudCom.

[32]  E. Baeyens,et al.  Wiener model identification and predictive control of a pH neutralisation process , 2004 .

[33]  O. Agamennoni,et al.  A nonlinear model predictive control system based on Wiener piecewise linear models , 2003 .

[34]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[35]  Er-Wei Bai,et al.  Decoupling the linear and nonlinear parts in Hammerstein model identification , 2004, Autom..

[36]  Ajay Mohindra,et al.  Resource Calculations with Constraints, and Placement of Tenants and Instances for Multi-tenant SaaS Applications , 2008, ICSOC.

[37]  Randy H. Katz,et al.  Above the Clouds: A Berkeley View of Cloud Computing , 2009 .

[38]  E. Baeyens,et al.  Hammerstein and Wiener model identification using rational orthonrmal bases , 2003 .

[39]  Xiaoyun Zhu,et al.  An adaptive optimal controller for non-intrusive performance differentiation in computing services , 2005, 2005 International Conference on Control and Automation.