Knowledge-based adaptable scheduler for SaaS providers in cloud computing

Human-centric Computing and Information Sciences

Volumn 5, Issue 1, 2015, Pages

  Motavaselalhagh, Farzaneh ^a   Safi Esfahani, Faramarz ^a   Arabnia, Hamid Reza ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b University of Georgia   (United States)

Author keywords

Admission control; Cloud computing; Data mining; Decision tree algorithm; Knowledge based; Scalability of application services; Service Level Agreement (SLA); Software as a service

Indexed keywords

ACCESS CONTROL; APPLICATION PROGRAMS; CLOUD COMPUTING; CUSTOMER SATISFACTION; DATA MINING; DECISION TREES; INFRASTRUCTURE AS A SERVICE (IAAS); INVESTMENTS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; PROFITABILITY; QUALITY OF SERVICE; SCHEDULING ALGORITHMS; TREES (MATHEMATICS); WEB SERVICES;

ADAPTABLE SCHEDULERS; DECISION-TREE ALGORITHM; KNOWLEDGE BASED; MACHINE LEARNING METHODS; SCALABILITY OF APPLICATION SERVICES; SERVICE LEVEL AGREEMENTS; SOFTWARE APPLICATIONS; VARIABLE PERFORMANCE;

SOFTWARE AS A SERVICE (SAAS);

EID: 84935033655     PISSN: None     EISSN: 21921962     Source Type: Journal    
DOI: 10.1186/s13673-015-0031-4     Document Type: Article

References (20)

1. Yeo CS, Buyya R (2005) Service level agreement based allocation of cluster resources: Handling penalty to enhance utility. In: Proceedings of the 7th IEEE International Conference on Cluster Computing (Cluster 2005), Boston, MA, USA
2. Lee YC, Wang C, Zomaya AY, Zhou BB (2010) Profit-driven service request scheduling in clouds, In: Proceedings of the International Symposium on Clusterand Grid Computing (CCGrid 2010), Melbourne, Australia
3. Microsoft Azure, http://azure.microsoft.com/, retrieved on 10 September, 2014.
4. Popovici I, Wiles J (2005) Profitable services in an uncertain world, In: Proceedings of the 18th Conference on Supercomputing (SC 2005), Seattle, WA
5. Saleforce, http://www.salesforce.com/au/, retrieved on 10 September, 2014.
6. Jaideep D and Varma M (2010) “Learning based Opportunistic admission control algorithms for map reduce as a service,” In Proceedings of the 3rd India Software Engineering Conference (ISEC 2010), Mysore, India
7. Bichler M, Setzer T, (2007) Admission control for media on demand services. Service oriented computing and application, In: Proceedings of IEEE International Conference on Service Oriented Computing and Applications (SOCA 2007), Newport Beach, California, USA
8. Broberg J, Venugopal S, Buyya R (2008) Market-oriented grids and utility computing: The state-of-the-art and future directions. Journal of Grid Computing 6:255–276
9. th International Heterogeneity in Computing Workshop (HCW 2009), in conjunction with the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS 2009), Roma, Italy
10. Varia J, Architecting applications for the Amazon Cloud, In: R. Buyya, J. Broberg, A. Goscinski (Eds.), Cloud Computing: Principles and Paradigms, Wiley Press, New York, USA, ISBN: 978-0470887998, 2010, http://aws.amazon.com
11. Mary NAB, “Profit Maximization for Service Providers using Hybrid Pricing in Cloud Computing,” International Journal of Computer Applications Technology and Research, vol. 2, pp. 218-223.
12. CIO, http://www.cio.com.au, retrieved on 10 September. 2010.
13. Calheiros RN, Ranjan R, Beloglazov A, De Rose CAF, Buyya R (2011) CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, Software: Practice and Experience (ISSN 0038-0644) 1 (41). Wiley Press, New York, USA, pp 23–50
14. Wu L, Kumar Garg S, Buyya R (2012) SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments. J Comput Syst Sci 78:1280–1299
15. Wu L, Garg SK, Buyya R (2011) “SLA-based resource allocation for software as a service provider (SaaS) in cloud computing environments,” in Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on
16. Liu Z, Squillante MS, and Wolf JL (2001) “On maximizing service-level-agreement profits,” In Proceedings of the 3rd ACM conference on Electronic Commerce, pp. 213-223
17. Reig G, Alonso J, Guitart J. Deadline constrained prediction of job resource requirements to manage high-level SLAs for SaaS cloud providers, Tech. Rep. UPC-DAC-RR, Dept. d’Arquitectura de Computadors, University Politécnica de Catalunya, Barcelona, Spain, 2010.
18. Mohana RS, Thangaraj P (2013) “Machine learning approchaches in improving Service Level Agreement-based admission control for software as a service provider in cloud”. J Comput Sci 9(10):1283–1294
19. Choi Y, Lim Y (2014) “Design of Cost Function for VM Allocation in Cloud Computing”. International Journal of Energy, Information and Communications 5(4):17–26
20. N. Ani Brown Mary, “Profit maximization for saas using sla based spot pricing cloud computing”, International Journal of Emerging Technology and Advanced Engineering, International Conference on Information Systems and Computing (ICISC-2013), INDIA, Volume 3, Special Issue 1, January 2013.