On the application of predictive control techniques for adaptive performance management of computing systems

被引：22

作者：

Abdelwahed, Sherif ^{[1
]}

Bai, Jia ^{[2
]}

Su, Rong ^{[3
]}

Kandasamy, Nagarajan ^{[4
]}

机构：

[1] Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State

[2] Institute for Software Integrated Systems, Vanderbilt University, Nashville

[3] Department of Mathematics and Computer Science, Eindhoven Univ. of Technology, Eindhoven

[4] Department of Electrical and Computer Engineering, Drexel University, Philadelphia

来源：

IEEE Transactions on Network and Service Management | 2009年 / 6卷 / 04期

基金：

美国国家科学基金会;

关键词：

Autonomic computing; Model-based management techniques; Power management of computing systems; Self-management of computing systems;

D O I：

10.1109/TNSM.2009.04.090402

中图分类号：

学科分类号：

摘要：

This paper addresses adaptive performance management of real-time computing systems. We consider a generic model-based predictive control approach that can be applied to a variety of computing applications in which the system performance must be tuned using a finite set of control inputs. The paper focuses on several key aspects affecting the application of this control technique to practical systems. In particular, we present techniques to enhance the speed of the control algorithm for real-time systems. Next we study the feasibility of the predictive control policy for a given system model and performance specification under uncertain operating conditions. The paper then introduces several measures to characterize the performance of the controller, and presents a generic tool for system modeling and automatic control synthesis. Finally, we present a case study involving a real-time computing system to demonstrate the applicability of the predictive control framework. © 2009 IEEE.

引用

页码：212 / 225

页数：13

共 41 条

[1]

Ganek A.G., Corbi T.A., The dawn of the autonomic computing era, IBM Syst. J., 42, 1, pp. 5-18, (2003)

[2]

Hellerstein J.L., Diao Y., Parekh S., Tilbury D.M., Feedback Control of Computing Systems, (2004)

[3]

Lu C., Stankovic J., Tao G., Son S., Feedback control real-time scheduling: Framework, modeling and algorithms, J. Real-Time Syst., 23, 1-2, pp. 85-126, (2002)

[4]

Cervin A., Eker J., Bernhardsson B., Arzen K., Feedbackfeedforward scheduling of control tasks, J. Real-Time Syst., 23, 1-2, (2002)

[5]

Liu X., Zhu X., Singhal S., Arlitt M., Adaptive entitlement control of resource containers on shared servers, Proc. 9th IFIP/IEEE Int'l Symp. Integrated Netw. Management (IM), pp. 163-176, (2005)

[6]

Abdelzaher T.F., Shin K.G., Bhatti N., Performance guarantees for web server end-systems: A control theoretic approach, IEEE Trans. Parallel Distributed Syst., 13, 1, pp. 80-96, (2002)

[7]

Parekh S., Et al., Using control theory to achieve service level objectives in performance management, Proc. IFIP/IEEE Int. Symp. Integrated Netw. Management, (2001)

[8]

Lu C., Alvarez G.A., Wilkes J., Aqueduct: Online data migration with performance guarantees, Proc. USENIX Conf. File Storage Tech., pp. 219-230, (2002)

[9]

Mascolo S., Classical control theory for congestion avoidance in highspeed internet, Proc. IEEE Conf. Decision Control, pp. 2709-2714, (1999)

[10]

Wang X., Chen M., Huang H.-M., Subramonian V., Lu C., Gill C., Control-based adaptive middleware for real-time image transmission over bandwidth-constrained networks, IEEE Trans. Parallel Distributed Syst., 19, 6, pp. 779-793, (2008)

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