In this paper we apply pole placement techniques to meet the performance objectives of a web server hosted on a private cloud. The web server is modeled as a switched system with models developed for several well defined operating regions using system identification technique. We then obtain the conditions for placement of exact and regional poles in desired locations using full state feedback to guarentee performance and stability. The experiments are performed on the open source Eucalyptus based cloud setup. © 2015 EUCA.

Ramkrishna Pasumarthy

Department of Electrical Engineering

Poles

Poles and zeros

State feedback

Web services

World Wide Web

Full state feedback

Operating regions

Performance guarantees

PERFORMANCE OBJECTIVE

Pole placement technique

PRIVATE CLOUDS

Switched system

System identification techniques

Feedback

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Performance guarantees via pole placement for a webserver hosted on a private cloud

2015 European Control Conference, ECC 2015

This paper presents the dynamic modeling and performance control of a Web server hosted on a private cloud. The cloud hosting Web server is a variable capacity system with two control inputs: 1) the number of virtual machines (VMs), which is indicative of the capacity of the cloud, and 2) the admission control used for regulating workload. As the workload and the hosting conditions change frequently, the linear parameter-varying (LPV) framework is well suited to derive the model. For the hosted Web server, we obtain an multiple input multiple output (MIMO) LPV model with performance metrics such as the response time and the throughput, which is then converted to polytopic LPV form using tensor product transformation. Finally, we design a gain scheduled linear quadratic regulator controller for performance guarantees with optimal cost of VMs. The identification, validation, and control experiments are demonstrated on the open source Eucalyptus cloud platform. The HTTP requests are generated using customized synthetic workload generator tool. © 1993-2012 IEEE.

IEEE Transactions on Control Systems Technology

Identification and Multivariable Gain-Scheduling Control for Cloud Computing Systems

This paper presents the performance management of a web-server hosted on a private cloud (the target system). Based upon an identified linear switched model with workload arrival rate as the switching signal, the paper presents a new algorithm to develop a multi-objective switching controller to ensure asymptotic stability with pole placement in convex regions called the DR-regions in the complex plane. These results are applied to the target system for performance guarantees in terms of the client perceived response time under changing workload conditions. The identification, validation and real-time control experiments are demonstrated on the open source Eucalyptus cloud platform. © 2016 Elsevier Ltd

Control Engineering Practice

Multi-objective switching controller for cloud computing systems

IEEE Transactions on Computers

Experience with CONSER: A System for Server Control through Fluid Modeling

Identification of LPV State Space Models for Autonomic Web Service Systems

Proceedings of the 2010 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems - SEAMS '10

Autonomic computing control of composed web services

Proceedings of the 18th ACM international symposium on High performance distributed computing - HPDC '09

Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters

Feedback Control of Computing Systems

Journal	Data powered by Typeset2015 European Control Conference, ECC 2015
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open Access	No