Abstract
Globalization has brought many changes in modern business world. Problems of enterprise oriented software applications like distribution and configuration of resources presents challenge to the traditional software sales model. Cloud computing presents the solution for such problems. With the help of cloud-based model one can earn good return by making the QoS demands of their users (customers) satisfied. In order to fulfill the infrastructure demands (like network, storage, etc.) to their users, service providers have to maintain their own hardware or they lease it from the IaaS providers.
For maintaining their own hardware SaaS providers will have to incur an extra cost, but if taken on lease, zero maintenance cost involved. Moreover, if provider wants to optimize cost and gain customer satisfaction, they will have to satisfy their customers/users by maintaining service level objectives. This paper presents a model for resource allocation in such a way as to minimize cost and maximize profit by satisfying the service level needs of the customers. The model is designed to enable the service providers with an ability to cope with the changing needs of customers, mapping customer requests to infrastructure level parameters and better handling of heterogeneous VMs.
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References
Ahuja, N., Kanungo, P., Katiyal, S., Parandkar, P.: Optimum management of resources in cloud computing environment: a challenge. In: International Conference on “Computing for Sustainable Global Development” INDIACom-2015organised by BVICAM, pp. 4–30 (2015)
Awasthi, C., Kanungo, P.: Resource allocation strategy for cloud computing environment. In: 2015 International Conference on Computer, Communication and Control (IC4), pp. 1–5 (2015). https://doi.org/10.1109/IC4.2015.7375716
Buyya, R., Garg, S.K., Calheiros, R.N.: Sla-oriented resource provisioning for cloud computing: challenges, architecture, and solutions. In: 2011 International Conference on Cloud and Service Computing, pp. 1–10. IEEE (2011)
Buyya, R., Ranjan, R., Calheiros, R.N.: InterCloud: utility-oriented federation of cloud computing environments for scaling of application services. In: Hsu, C.-H., Yang, L.T., Park, J.H., Yeo, S.-S. (eds.) ICA3PP 2010. LNCS, vol. 6081, pp. 13–31. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13119-6_2
Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, C.A., Buyya, R.: Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Soft. Pract. Experience 41(1), 23–50 (2011)
Goudarzi, H., Pedram, M.: Maximizing profit in cloud computing system via resource allocation. In: 2011 31st International Conference on Distributed Computing Systems Workshops, pp. 1–6 (2011). https://doi.org/10.1109/ICDCSW.2011.52
Mehta, H.K., Kanungo, P., Chandwani, M.: Performance enhancement of scheduling algorithms in web server clusters using improved dynamic load balancing policies (2008)
Parikh, S.: A survey on cloud computing resource allocation techniques, pp. 1–5 (2013). https://doi.org/10.1109/NUiCONE.2013.6780076
Saxena, R., Dey, S.: Cloud shield: effective solution for DDoS in cloud. In: Di Fatta, G., Fortino, G., Li, W., Pathan, M., Stahl, F., Guerrieri, A. (eds.) IDCS 2015. LNCS, vol. 9258, pp. 3–10. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23237-9_1
Saxena, R., Dey, S.: A novel access control model for cloud computing. In: Li, E., et al. (eds.) IDCS 2016. LNCS, vol. 9864, pp. 81–94. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45940-0_8
Saxena, R., Dey, S.: Light weight access control mechanism for mobile-based cloud data storage. Int. J. Next Gener. Comput. 9(2) (2018). http://perpetualinnovation.net/ojs/index.php/ijngc/article/view/424
Saxena, R., Dey, S.: On-demand integrity verification technique for cloud data storage. Int. J. Next Gener. Comput. 9(1) (2018). http://perpetualinnovation.net/ojs/index.php/ijngc/article/view/425
Saxena, R., Dey, S.: Data integrity verification: a novel approach for cloud computing. Sādhanā 44(3), 1–12 (2019). https://doi.org/10.1007/s12046-018-1042-4
Wu, L., Garg, S., Buyya, R.: Sla-based admission control for a software-as-a-service providerin cloud computing environments (2012). https://doi.org/10.1016/j.jcss.2011.12.014
Wu, L., Garg, S.K., Buyya, R.: Sla-based resource allocation for software as a service provider (SaaS) in cloud computing environments. In: 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 195–204 (2011). https://doi.org/10.1109/CCGrid.2011.51
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Saxena, R., Dubey, S., Sada, R. (2023). Efficient Approach for Virtual Machine and Resource Allocation in Cloud Computing. In: Garg, L., et al. Key Digital Trends Shaping the Future of Information and Management Science. ISMS 2022. Lecture Notes in Networks and Systems, vol 671. Springer, Cham. https://doi.org/10.1007/978-3-031-31153-6_11
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