Abstract
Cloud computing is an emerging technology that have a broad scope to offers a wide range of services to revolutionize the existing IT infrastructure. This internet based technology offers a services like – on demand service, shared resources, multitenant architecture, scalability, portability, elasticity and giving an illusion of having an infinite resource by a consumer through virtualization. Because of the elastic nature of a cloud it is very critical of a service provider specially for a small/medium cloud provider to form a viable SLA with a consumer to avoid any service violation. SLA is a key agreement that need to be intelligently form and monitor, and if there is a chance of service violation then a provider should be informed to take necessary remedial action to avoid violation. In this paper we propose our viable SLA management framework that comprise of two time phases – pre-interaction time phase and post-interaction time phase. Our viable SLA framework help a service provider in making a decision of a consumer request, offer the amount of resources to consumer, predict QoS parameters, monitor run time QoS parameters and take an appropriate action to mitigate risks when there is a variation between a predicted and an agreed QoS parameters.
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Bahtovski, A., Gusev, M.: Analysis of cloud portability. In: The 10th Conference for Informatics and Information Technology, pp. 280–284 (2013)
Gartner, I.: Forecast: public cloud services. Worldwide, 2013-2019 (2016). (Gartner )
Hussain, W., Hussain, F.K., Hussain, O.K.: Maintaining trust in cloud computing through SLA monitoring. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds.) ICONIP 2014, Part III. LNCS, vol. 8836, pp. 690–697. Springer, Heidelberg (2014)
Hussain, W., et al.: Profile-based viable service level agreement (SLA) violation prediction model in the cloud. In: 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), Krakow, Poland, pp. 268–272. IEEE (2015)
Hussain, W., Hussain, F.K., Hussain, O.: Allocating optimized resources in the cloud by a viable SLA model. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, Vancouver, Canada (2016)
Hussain, W., et al.: Provider-based optimized personalized viable SLA (OPV-SLA) framework to prevent SLA violation. Comput. J., 24 (2016)
Macias, M., Guitart, J.: A risk-based model for service level agreement differentiation in cloud market providers. In: Magoutis, K., Pietzuch, P. (eds.) DAIS 2014. LNCS, vol. 8460, pp. 1–15. Springer, Heidelberg (2014)
Liu, D., Kanabar, U., Lung, C.-H.: A light weight SLA management infrastructure for cloud computing. In: 2013 26th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE (2013)
Morin, J.-H., Aubert, J., Gateau, B.: Towards cloud computing SLA risk management: issues and challenges. In: 2012 45th Hawaii International Conference on System Science (HICSS). IEEE (2012)
Hussain, W., Hussain, F.K., Hussain, O.: Comparative analysis of consumer profile-based methods to predict SLA violation. In: FUZZ-IEEE. IEEE, Istanbul Turkey (2015)
Hussain, W., Hussain, F.K., Hussain, O.: QoS prediction methods to avoid SLA violation in post-interaction time phase. In: 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016). IEEE, Hefei (2016)
Hussain, W., Hussain, F.K., Hussain, O.K.: Towards soft computing approaches for formulating viable service level agreements in cloud. In: Arik, S., Huang, T., Lai, W.K., Liu, Q. (eds.) ICONIP 2015. LNCS, vol. 9492, pp. 639–646. Springer, Heidelberg (2015). doi:10.1007/978-3-319-26561-2_75
Zhang, Y., Zheng, Z., Lyu, M.R.: WSPred: a time-aware personalized QoS prediction framework for Web services. In: 2011 IEEE 22nd International Symposium on Software Reliability Engineering (ISSRE). IEEE (2011)
CloudClimate: Watching the Cloud. http://www.cloudclimate.com/
Monitor, P.N.: PRTG Network Monitor. https://prtg.paessler.com/
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Hussain, W., Hussain, F.K., Hussain, O.K. (2016). SLA Management Framework to Avoid Violation in Cloud. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9949. Springer, Cham. https://doi.org/10.1007/978-3-319-46675-0_34
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DOI: https://doi.org/10.1007/978-3-319-46675-0_34
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