Abstract
With its rapid evolution, cloud computing has become a complex ecosystem characterized by the diversity of service descriptions and prices, the heterogeneity of virtualization technologies and APIs used. It is increasingly difficult for users to compare and choose the services that best meet needs at optimal cost. In this paper, we model the user request as a graph, nodes describe virtual machines and edges represent network requirements. We propose a mathematical formulation of an integer linear program (ILP) to select a set of IaaS services, which define a cost-effective cloud resources allocation plan, according to the user request graph. A performance evaluation is reported to assess the efficiency and scalability of the proposed algorithm.
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References
Riane, D., Ettalbi, A.: Efficient and optimal service component distribution across multiple clouds. Int. J. Rec. Contrib. Eng. Sci. IT (iJES). 6(3), 44–59 (2018)
Riane, D., Ettalbi, A.: A graph-based approach for composite infrastructure service deployment in multi-cloud environment. In: International Conference on Advanced Communication Technologies and Networking, pp. 1–7, Marrakech, Morocco (2018)
Raugust, A.S., de Souza, F.R., Pillon, M.A., Miers, C.C., Koslovski, G.P.: Allocation of virtual infrastructures on multiple IaaS providers with survivability and reliability requirements. In: IEEE 32nd International Conference on Advanced Information Networking and Applications, pp. 1147–1154, Krakow, Poland (2018)
Ran, Y., Yang, B., Cai, W., XI, H., Yang, J.: Cost-efficient provisioning strategy for multiple services in distributed clouds. In: IEEE International Conference on Cloud Computing Research and Innovations, pp. 1–8, Singapore (2016)
Mistry, S., Bouguettaya, A., Dong, H., Qin, A. K.: Metaheuristic optimization for long-term IaaS service composition. IEEE Trans. Serv. Comput. 11(1), 131–143 (2018)
Prachitmutita, I., Aittinonmongkol, W., Pojjanasuksakul, N., Supattatham, M., Padungweang, P.: Auto-scaling microservices on IaaS under SLA with cost-effective framework. In: 10th International Conference on Advanced Computational Intelligence, pp. 583–588, Xiamen, China (2018)
Tsakalozos, K., Verroios, V., Roussopoulos, Delis, A.: Live VM migration under time-constraints in share-nothing IaaS-clouds. IEEE Trans. Parallel Distrib. Syst. 28(8), 2285–2298 (2017)
Li, J., Zhu, Y., Yu, J., Long, C., Xue, G., Qian, S.: Online auction for IaaS clouds- towards elastic user demands and weighted heterogeneous VMs. In: IEEE Conference on Computer Communications, pp. 1–9, Atlanta, GA, USA (2017)
Zhou, Y., Hoffmann, H., Wentzlaff, D.: CASH: Supporting IaaS customers with a subcore configurable architecture. In: ACM/IEEE 43rd Annual International Symposium on Computer Architecture, pp. 682–694, Seoul, Korea (2016)
Metwally, K., Jarray, A., Karmouch, A.: A cost-efficient QoS-aware model for cloud IaaS resource allocation in large datacenters. In: IEEE 4th International Conference on Cloud Networking, pp. 38–43, Niagara Falls, ON, Canada (2015)
Takfarinas, S., Thorburn, J., Murphy, L., and Ventresque, A.: VM reassignment in hybrid clouds for large decentralized companies: a multi-objective challenge. Future Gen. Comput. Syst. 79(2), 751–764 (2018)
Portal, G.M., Ritt, M., Borba, L.M., Buriol, L.S.: Simulated annealing for the machine reassignment problem. Ann. Oper. Res. 242, 93–114 (2016)
Laalaoui, Y., Al-Omari, J.: A planning approach for reassigning virtual machines in IaaS clouds. IEEE Trans. Cloud Comput. 8(3), 685–697 (2020)
Riane, D., Ettalbi, A.: Towards a clustering-based approach to speed up IaaS Service discovery process. In: International Conference on Advanced Communication Technologies and Networking, pp. 1–5, Rabat, Morocco (2019)
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Riane, D., Ettalbi, A. (2023). ILP-Based Approach for Cloud IaaS Composition. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 715. Springer, Cham. https://doi.org/10.1007/978-3-031-35507-3_51
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DOI: https://doi.org/10.1007/978-3-031-35507-3_51
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