Research on the resource monitoring model under cloud computing environment

Authors:
Junwei Ge;Bo Zhang;Yiqiu Fang
Affiliations:
College of software, Chongqing University of Posts and Telecommunications, Chongqing, China;College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Venue:
WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
Year:
2010

Citing 4
Cited 1

A Flexible Monitoring and Notification System for Distributed Resources

ISPDC '08 Proceedings of the 2008 International Symposium on Parallel and Distributed Computing
WSRF-Based Distributed Visualization

CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
The Eucalyptus Open-Source Cloud-Computing System

CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Integrating the common information model with MDS4

GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing

HSGA: a hybrid heuristic algorithm for workflow scheduling in cloud systems

Cluster Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Resource monitoring is an important part of resource management under the cloud computing environment, which provides a better reference for resource allocation, task scheduling and load balancing. Because of the commercial applications target of billing the user for the use of resources, the high virtualization, scalability and transparency of the cloud computing environment's resources, the existing resource monitoring methods of both distributed computing and grid computing can not satisfy the cloud computing environment completely. So, according to the characteristics of cloud computing platforms, we present a novel resource monitoring model appropriately adapted to cloud computing environment, which combines VMM (Virtual Machine Monitor) and the C/C++ called by Java to obtain the information of the resource status. Both theoretical analysis and experiments results show that the model can be used to collect resource monitoring information on nodes and VM (virtual machine), which not only meets the requirements of cloud computing platform features but also has a good property of effectiveness.