Abstract
Cloud ERP solutions, providing business processes automation and improving visibility across the whole enterprise, are the highest growth segment of the ERP software industry. One of the important challenges faced by cloud ERP providers is the effective management of cloud services performance. Cloud ERP clients and cloud service providers have different goals. Users want to minimize their expenses while meeting the cloud ERP performance requirements. The main goal of a cloud service provider is the profit maximization through decreasing service costs and reducing the number of violations to the quality of service provided. The effective resource management and provisioning is still a challenging task for cloud computing providers because of the high variability of workload over time. On the one hand, cloud providers can respond to most of the queries owning only a restricted amount of resources, but this results in customers’ requests rejection during peak hours. On the other hand, valley hours incur in over-provisioning of the resources, which forces the providers to increase their prices to be profitable. This paper represents cloud ERP query flow control model, built in Powersim, supporting cloud provider’s decision-making process of resource allocation and cloud services portfolio management in order to achieve profit optimization, based on quality restrictions and query flow control mechanism.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Amazon Amazon elastic compute cloud, http://aws.amazon.com/ec2/
ERP Software Systems Index for Manufacturing, http://www.top10erp.org/erp-software-comparison-cloud-based-saas-platform-566
Onlanta, http://onlanta.ru/
Plex Systems, http://www.plex.com/
Powersim, http://www.powersim.com/
Salesforce, http://www.salesforce.com/eu/?ir=1
Hao-peng, C., Li, S.-C.: A queueing-based model for performance management on cloud. In: 6th International Conference on Advanced Information Management and Service (IMS), November 30-December 2 (2010)
Chen, J.L., et al.: Profit-driven Cloud Service Request Scheduling Under SLA constraints, http://www.joics.com/publishedpapers/2012_9_14_4065_4073.pdf
Lee., C.Y., et al.: Profit-driven Service Request Scheduling in Clouds, http://sydney.edu.au/engineering/it/research/tr/tr646.pdf
Devore, J.L.: Probability and Statistics for Engineering and Sciences, 6th edn. Thomson Learning, Inc., Toronto (2004)
Leif, G.: Poisson Simulation outperforms Markov Simulation, http://www.signal.uu.se/Research/simulation/PoS_Markov_22.pdf
Charles, M.M., North, M.J.: Introduction to Agent-based Modeling and Simulation., http://www.mcs.anl.gov/~leyffer/listn/slides-06/MacalNorth.pdf
Mankiw, G.: Principles of economics. South-Western Pub. (2008)
McManus, M.L., Long, M.C., Copper, A., Litavak, E.: Queuing theory accurately models the need for critical care resources. Anesthesiology 100(5), 1271–1276 (2004) (ISSN 0003-3022)
Patil, S.D., Mehrotra, S.C.: Resource allocation and Scheduling in the Cloud. International Journal of Emerging Trends and Technology in Computer Science (IJETTCS)Â 1 (2012) www.ijettcs.org
Page Ernest Jr., H.: Simulation Modeling Methodology: Principles and Etiology of Decision Support, http://thesimguy.com/articles/simModMeth.pdf
Jelena, R.: Stochastic Models of Data Flows In The Telecommunication Networks, http://www.tsi.lv/Research/Conference/RelStat_09/Proceedings/Sess_2_Revzina.pdf
Rummery, G., Niranjan, M.: On-line Q-learning using connectionist systems. Engineering Department, Cambridge University, New Zealand (1994)
Michele, S.: Modelling and simulation of complex systems, http://eco83.econ.unito.it/dottorato/michele_sonnessa/sonnessa_thesis.pdf
Wolff, R.W.: Poisson arrivals see time averages. Oper. Res. 30(2), 223–231 (1998)
Liu, Z., Sun, Q., Wang, S., Zou, H., Yang, F.: Profit-driven Cloud Service Request Scheduling Under SLA Constraints. Journal of Information & Computational Science 9(14), 4065–4073 (2012)
Forrester, J.W.: System dynamics, system thinking and soft OR//. System Dynamics Review 10(2) (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Romanov, V., Varfolomeeva, A. (2013). Cloud ERP Query Flow Control Simulation with Quality Restrictions and Profit Gaining Criteria. In: Barjis, J., Gupta, A., Meshkat, A. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2013. Lecture Notes in Business Information Processing, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41638-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-41638-5_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41637-8
Online ISBN: 978-3-642-41638-5
eBook Packages: Computer ScienceComputer Science (R0)