Novel Methods For Determining QoS Parameters and Thresholds in End User's Service Level Agreement

Document Type : Research Article

Authors

1 Department of Communication Technology, ICT Research Institute (ITRC),Tehran ,Iran

2 Department of Communication Technology, ICT Research Institute (ITRC),Tehran ,Iran

3 Department of Communication Technology, ICT Research Institute (ITRC),Tehran ,Iran

4 Department of Communication Technology, ICT Research Institute (ITRC),Tehran ,Iran.

Abstract

Service level agreement (SLA) is a powerful tool to formalize the negotiation and agreement between the service provider and service seeker with the scope of service quality characteristics, compensations and tariffs. The service quality description is the main part of a SLA which can be characterized by the use of suitable and feasible quality of service (QoS) parameters. Determining suitable QoS parameters is the most important step in SLA codification. In this paper, we propose a novel method for determining the most related QoS parameters for characterizing the service quality in a service level agreement. The proposed method is a step-by-step algorithm which is based on selecting feasible parameters among a general initial list obtained from international references. The criteria for feasibility is perceivability and measurability from end user view point. Our method is general and can be applied for each service. We also leverage on clustering algorithm to prioritize the feasible QoS parameters according to their popularity in international studies. Finally, we propose a statistical method to determine the threshold for the feasible parameters. We provide an interval for each threshold. We show the steps of our proposed methods via a case study as the final part of the paper.

Keywords

Main Subjects


[1] T. Trygar and G. Bain, A framework for service level agreement management, IEEE Military Communications Conference (MILCOM), 1 (2005) 331–337.
 
[2] E. Marilly, O. Martinot, S. Betge-Brezetz, and G. Delegue, Requirements for service level agreement management, IEEE Workshop on IP Operations and Management, (2002) 57–62.
 
[3] B. Lee and G. Lee, Service oriented architecture for SLA management system, The 9th International Conference on Advanced Communication Technology, 2 (2007) 1415–1418.
 
[4] A. Alqahtani, Y. Li, P. Patel, E. Solaiman, and R. Ranjan, End-to-end service level agreement specification for IoT applications, International Conference on High Performance Computing Simulation (HPCS) (2018) 926–935.
 
[5] S. Pandey, A. Upadhaya, and C. Jha, Need of SLA parameters in cloud environment. An evaluation, International Journal of Computer Science Engineering and Technology (IJCSET), 7 (12) (2016) 484–490.
 
[6] N. Ghosh and S. K. Ghosh, An approach to identify and monitor SLA parameters for storage-as-a-service cloud delivery model, IEEE Globecom Workshops, (2012) 724– 729.
 
[7] I. Goiri, F. Julia, J. O. Fito, M. Mac─▒as, and J. Guitart, Supporting cpu-based guarantees in
cloud slas via resource-level qos metrics, Future Generation Computer Systems, 28 (8) (2012) 1295–1302.
 
[8] A. Paschke and E. Schnappinger-Gerull, A categorization scheme for SLA metrics, Service-Oriented Electronic Commerce, Proceedings zur Konferenz im Rahmen der Multikonferenz Wirtschaftsinformatik 2006. Gesellschaft f¨ur Informatik eV, (2006).
 
[9] M. Fugini and H. Siadat, SLA contract for cross-layer monitoring and adaptation,  International Conference on Business Process Management,  (2009) 412– 423.
 
[10] Q. He, J. Yan, R. Kowalczyk, H. Jin, and Y. Yang, An agent-based framework for
service level agreement management, IEEE International Conference on Computer Supported Cooperative Work in Desig, (2007) 412-417.
 
[11] H. J. Lee, M. S. Kim, and J. W. Hong, Mapping between QoS parameters and network performance metrics for SLA monitoring, Asia-Pacific Network Operations and Management Symposium (APNOMS), (2002) 97-108.
 
[12] R. S. Gracia, Y. Labit, J. D. Pascual, and P. Owezarski, Towards an efficient service level agreement assessment, IEEE INFOCOM, (2009) 2581-2585.
 
[13] B. Y. Lee and G. H. Lee, Service oriented architecture for SLA management system,
IEEE International Conference on Advanced Communication Technology, 2 (2007) 1415-1418.
 
[14] International Telecommunication Union, Framework of a service level agreement, ITU-T
E.860, (2002).
 
[15] European Telecommunications Standards Institute, Quality of telecom services; part 3: Template for service level agreements (SLA), ETSI-EG 202 009-3, (2006).
 
[16] T. Forum, SLA management handbook: Volume 2 concepts and principles, TM Forum, (2005).
 
[17] Information Technology Infrastructure Library, Glossary of terms, definitions and acronyms, ITIL, (2007).
 
[18] International Telecommunication Union, Definitions of terms related to quality of service,
ITU-T E.800, (2008).
 
[19] I. Rish ,An empirical study of the naive bayes classifier, IJCAI 2001 workshop on empirical methods in artificial intelligence, 3 (22) (2001) 41–46.
 
[20] W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Section 16.5. support
vector machines, Numerical recipes: the art of scientific computing, (2007).
 
[21] J. R. Quinlan, Induction of decision trees, Machine learning, 1(1) 81–106 (1986).
 
[22] S. Balakrishnama and A. Ganapathiraju, Linear discriminant analysis-a brief tutorial, Institute for Signal and information Processing, 18 (1998) 1–8.
 
[23] T. Denoeux, A k-nearest neighbor classification rule based on dempster-shafer theory, Classic works of the Dempster-Shafer theory of belief functions. Springer, (2008) 737–760.
 
[24] J. A. Hartigan and M. A. Wong, Algorithm as 136: A k-means clustering algorithm, Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1) (1979) 100–108.
 
[25] N. Mehra and S. Gupta, Survey on multiclass classification methods, Neural Netw, (2013) 1-9.
 
[26] H. H. Ali and L. E. Kadhum, K-means clustering algorithm applications in data mining and pattern recognition, International Journal of Science and Research, 6 (8) (2017) 1577–1584.
 
 
[28] J. de Mast, G. Diepstraten, and R. J. Does, Quality quandaries: Design for six sigma: Method and application, Quality Engineering, 23 (2) (2011) 204–211.
 
[29] R. Schenkendorf, A. Kremling, and M. Mangold, Optimal experimental design with the sigma point method, IET systems biology, 3 (1) (2009)10–23.
 
[30] R. D. Snee, Impact of six sigma on quality engineering, Quality Engineering, 12 (3) (2000) 9–14.
 
[31] Available from:  https://www.fcc.gov.
 
[32] Available from:  https://www.ofcom.org.uk.
 
[33] Available from:  https://main.trai.gov.in.
 
[34] Available from:  https://www.tra.org.bh.
 
[35] Available from:  www.tk.gov.tr.
 
[36] Available from:  www.cmc.gov.my.
 
[37] Available from:  www.ida.gov.sg.
 
[38] Available from:  https://www.cra.ir.
 
[39] Available from:  http://www.tra.gov.eg.
 
[40] Available from:  https://www.att.com/.
 
[41] Available from:  https://www.verizon.com.
 
[42] Available from:  http://batelco.com/.
 
[43] Available from:  https://www.zain.com/en/.
 
[44] Available from:  https://www.bsnl.co.in/.
 
[45] Available from:  https://www.tm.com.my.
 
[46] Available from:  https://www.turktelekom.com.tr.
 
[47] Available from:  https://www.vodafone.com/.
 
[48] Available from:  https://www.bt.com/.
 
[49] Available from:  https://www.singtel.com/.
 
[50] Available from:  https://www.starhub.com.
 
[51] T. Janevski, QoS for Fixed and Mobile Ultra-Broadband. Wiley Telecom, (2019).