Title: Sharing computing resources to satisfy multi-cloud user requirements

Authors: N. Xiong; Andy Rindos; M.L. Russell; K.P. Robinson; A. Vandenberg; Yi Pan

Addresses: Department of Computer Science, Georgia State University, 34 Peachtree Street, #1428, Atlanta, GA, 30303, USA; Information Systems and Technology, Georgia State University, Commerce Building, 34 Broad Street, Atlanta, GA, 30303, USA. ' IBM Corporation, 3039 Cornwallis Rd., 27709, Research Triangle Park, NC, USA. ' Information Systems and Technology, Georgia State University, Commerce Building, 34 Broad Street, Atlanta, GA, 30303, USA. ' Information Systems and Technology, Georgia State University, Commerce Building, 34 Broad Street, Atlanta, GA, 30303, USA. ' Information Systems and Technology, Georgia State University, Commerce Building, 34 Broad Street, Atlanta, GA, 30303, USA. ' Department of Computer Science, Georgia State University, 34 Peachtree Street, #1442, Atlanta, GA, 30303, USA

Abstract: In this paper, we first propose a system model for a multi-cloud environment, which we define as a network of clouds that may interoperate to serve their individual user bases in each local intra-cloud. Local clouds may share services among other clouds in order to load balance or meet peak demands. Using this model, we propose an effective proportional and integral feedback control scheme based on control theory to share limited resources to satisfy requirements of multiple users wanting fast response and/or high utilisation of cloud resources. Our control scheme is based on a self-tuning feedback theory, which considers not only the actual versus target value of resource utilisation, but also the history of application computing rates. After that, we provide a theoretical analysis of the system stability and give guidelines for selection of feedback control parameters to stabilise the resource utilisation at a desirable target level. Simulations have been conducted to demonstrate that this proposed scheme can be an effective multi-cloud computing controller for ensuring fast response and high resource utilisation. Finally, we also analysed the distribution rate of Georgia State University student technology fee, and it is required that VCL could use fewer fees to support more required service.

Keywords: cloud computing; control theory; high performance computing; HPC; resource allocation; virtual computing; multi-cloud environments; self-tuning control; feedback control; simulation; resource sharing.

DOI: 10.1504/IJCC.2011.043247

International Journal of Cloud Computing, 2011 Vol.1 No.1, pp.81 - 100

Received: 11 Feb 2011
Accepted: 29 Mar 2011
Published online: 30 Dec 2014 *

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