Home   >   CSC-OpenAccess Library   >    Manuscript Information
Resource Monitoring Algorithms Evaluation For Cloud Environment
Mostafa M. Al-Sayed, Shrerif M. Khattab, Fatma A. Omara
Pages - 159 - 174     |    Revised - 15-11-2013     |    Published - 15-12-2013
Volume - 7   Issue - 5    |    Publication Date - December 2013  Table of Contents
Cloud Computing, Resource Monitoring, Virtualization, Scalability.
Cloud computing is a type of distributed computing allowing to share many resources such as CPU, memory, storage ...etc. The status of these resources changes from time to time due to the dynamic adaptive ability of the cloud computing characteristics. Hence, the powerful and scalable monitoring algorithm is needed to monitor the status of these resources throughout the time. There are many models have been proposed for monitoring the distributed systems resources; the push-based, the pull-based, and the push/pull model. Most of the common monitoring systems are based on these models (e.g., Ganglia which based on push model and Nagios, which based on pull model). According to the work in this paper, a comparative study has been done to implement and evaluate these three models on the cloud environment. The implementation results showed that the push-based model outperforms the other two models due to its high scalability, stability, and efficiency.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
A. Cooke, A.J.G. Gray, L. Ma, and W. Nuttetal (2003), “R-GMA: an information integration system for grid monitoring,” Proceedings of the 11th International Conference on Cooperative, Information Systems, Catania, Sicily, Italy , PP 462–481.
B. S. Ghio, (March 2012). Project of a SDP prototype for Public Administrations and private networks. Faculty of Mathematics, Physics and Natural Sciences, University of Genoa.Master of Science in Information Technology.
B. Tierney, R. Aydt, D. Gunter, W. Smith, M. Swany, V. Taylor, and R. Wolski (August 2002),“A Grid Monitoring Architecture,” The Global Grid Forum Draft Recommendation (GWD-Perf-16-3).
C. Wang, K. Schwan, V. Talwar, G. Eisenhauer, L. Hu, and M. Wolf (2011), “A flexible architecture integrating monitoring and analytics for managing large-scale data centers,”Proceedings of the 8th International Conference on Autonomic Computing, Ser. ICAC’11, ACM, New York, NY, USA, PP 141–150.
Cloud Computing: Principles and Paradigms, Edited by R. Buyya, J. Broberg and A. Goscinski © 2011 John Wiley & Sons, Inc.
F. Wuhib, R. Stadler (2011). Distributed Monitoring and Resource Management For Large Cloud Environments. KTH R. Inst. of Technol., Stockholm, Sweden. PhD Thesis.
G. Katsaros, R. Kübert, and G. Gallizo (2011), “Building a service-oriented monitoring framework with REST and nagios,” IEEE International Conference on Services Computing(SCC), Washington, DC, PP 426–431.
Ganglia: http://ganglia.sourceforge.net.
H. Fang-fang, P. Jun-jie, Z. Wu, L. Qing, L. Jian-dun, J. Qin-long, Y. Qin (Oct 2011), "Virtual Resource Monitoring in Cloud Computing," Journal of Shanghai University, 15, PP 381-385.
H. Huang, L. Wang (Jul 2010), “P&P: A Combined Push-Pull Model for Resource Monitoring in Cloud Computing Environment,” 3rd IEEE International conference on Cloud Computing (CLOUD 2010). Miami, FL, PP 260 – 267.
H. Newman, I. Legrand, P. Galvez, R. Voicu, and C. Cirstoiu (2003), “MonALISA: a distributed monitoring service architecture,” Computing in High Energy and Nuclear Physics 2003 Conference Proceedings (CHEP03), California, USA.
I. Foster, Y. Zhao, I. Raicu, and S. Lu. (2008), “Cloud computing and Grid computing 360- degree compared”, Grid Computing Environments Workshop, Austin, TX, PP 1-10.
J. Brandt, A. Gentile, J. Mayo, P. Pebay, D. Roe, D. Thompson, M. Wong (May 2009),“Resource Monitoring and Management with OVIS to Enable HPC in Cloud Computing Environments,” 23rd IEEE International Parallel & Distributed Processing Symposium (5thWorkshop on System Management Techniques, Processes, and Services). Rome, Italy, PP1 – 8.
J. Ge, B. Zhang, Y. Fang (2010), "Research on the Resource Monitoring Model Under Cloud Computing Environment," The International Conference on Web Information Systems and Mining (WISM'10). Sanya, China, PP 111-118.
J. Park, K. Chung, E. Lee, Y. Jeong, H. Yu (May 2010), “Monitoring Service Using Markov Chain Model in Mobile Grid Environment,” the 5th international conference on Advances in grid and pervasive computing (GPC 2010). Hualien, Taiwan, PP 193-203.
J. S. Ward & A. Barker (2012), “Semantic Based Data Collection for Large Scale Cloud Systems”, DIDC '12 Proceedings of the fifth international workshop on Data-Intensive Distributed Computing Date, New York, USA.
J.S. Park, H.C. Yu, K.S. Chung, and E.Y. Lee (2011), “Markov chain based monitoring service for fault tolerance in mobile cloud computing,” IEEE Workshops of International Conference on Advanced Information Networking and Applications (WAINA), Biopolis , PP 520–525.
M. Kutare, G. Eisenhauer, C. Wang, K. Schwan, V. Talwar, and M. Wolf (2010), “Monalytics:online monitoring and analytics for managing large scale data centers,” Proceedings of the 7th International Conference on Autonomic Computing, Ser. ICAC ‘10, ACM, New York, NY,USA, PP 141–150.
M. Wu & X.H. Sun. (2006), “Grid harvest service: a performance system of Grid computing,”Journal of Parallel and Distributed Computing, 66(10): 1322-1337.
M.L. Massie, B.N. Chun, and D.E. Culler (2003), “The ganglia distributed monitoring system: design, implementation and experience,” Parallel Computing, 30(7): 817-840.
Nagios, available in: http://www.nagios.org.
R. Bhatnagar & J. Patel (2013), "Performance Analysis of A Grid Monitoring System -Ganglia." International Journal of Emerging Technology and Advanced Engineering 3(8):362-365.
R. Sundaresan, M. Lauria, T. Kurcy, S. Parthasarathy, J. Saltz (June 2003), “Adaptive Polling of Grid Resource Monitors Using a Slacker Coherence Model,” The 12th IEEE International Symposium on High Performance Distributed Computing (HPDC’03). Seattle, Washington, PP 260-269.
S. Andreozzi, N. De Bortoli, S. Fantinel, A. Ghiselli, G.L. Rubini, G. Tortone, and M.C. Vistoli (2005), “GridICE: a monitoring service for grid systems,” Future Generation Computer Systems 21(4): PP 559–571.
S. Clayman, R. Clegg, L. Mamatas, G. Pavlou, and A. Galis (2011), “Monitoring, aggregation and filtering for efficient management of virtual networks,” Proceedings of the 7th International Conference on Network and Services Management, Paris, PP 1–7.
W. Chung, R. Chang (2009), "A New Mechanism For Resource Monitoring in Grid Computing," Future Generation Computer Systems - FGCS 25, PP 1-7.
Mr. Mostafa M. Al-Sayed
Faculty of Computers and Information Minia University Minia - Egypt
Dr. Shrerif M. Khattab
Faculty of Computers and Information Cairo University Cairo - Egypt
Professor Fatma A. Omara
Faculty of Computers and Information Cairo University Cairo - Egypt

View all special issues >>