Abstract
Mobile cloud refers to a cloud network which supports mobility. The mobility provides a lot of benefits including the fast execution of user request and less wastage of resources. To encompass the services, the cloudlet use virtual machines (VMs) which not only share the load of the cloudlet but also increases the processing speed. This paper presents a unique allocation and utilization policy of mobile cloud which uses load management and VM allocation and migration policy to provide the best services to the user. The VM selection is complete via support vector machine (SVM). The paper uses modified best fit decreasing (MBFD) algorithm to settle down the VMs in the mobile environment.
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References
Mell, P., Grance, T.: The NIST Definition of Cloud Computing. National Institute of Standards and Technology: U.S. Department of Commerce, NIST Special Publication 800-145.
Huang, D., Xing, T., Wu, H.: Mobile cloud computing service models: a user-centric approach. IEEE Netw. 27(5), 6–11 (2013)
Li, X., Du, J.: Adaptive and attribute-based trust model for service level agreement guarantee in cloud computing. IET Inf. Secur. 7(1), 39–50 (2013)
Gonzales, D., Kaplan, J., Saltzman, E., Winkelman, Z., Woods, D.: Cloud-trust—a security assessment model for infrastructure as a service (IaaS) clouds. IEEE Trans. Cloud Comput. 5(3), 523–536 (2017)
Ahmed, M.T., Hussain, A.: Survey on energy-efficient cloud computing systems. Int. J. Adv. Eng. Res. 5(II), (2013). ISSN: 2231-5152
Esfandiarpoor, S., Pahlavan, A., Goudarzi, M.: Virtual machine consolidation for datacenter energy improvement. arXiv preprint arXiv:1302.2227 (2013)
Bertini, L., Leite, J.C., Mossé, D.: Power optimization for dynamic configuration in heterogeneous web server clusters. J. Syst. Softw. 83(4), 585–598 (2010)
Ahmad, R., Gani, A., Ab, S., Shiraz, H., Xia, F., Madani, S.: Virtual machine migration in cloud data centers: a review, taxonomy, and open research issues. J. Supercomput. 2473–2515 (2015)
Sonkar, S., Thorat, A.: A Review on Dynamic Consolidation of Virtual Machines for Effective Utilization of Resources and Energy Efficiency in Cloud (2016)
Speitkamp, B., Bichler, M.: A mathematical programming approach for server consolidation problems in virtualized data centers. IEEE Trans. Serv. Comput. 3(4), 266–278 (2010)
Tucker, R., Hinton, K., Ayre, R.: Energy-efficiency in cloud computing and optical networking. In: 2012 38th European Conference and Exhibition on Optical Communications, pp. 1–32. Amsterdam (2012)
Wajid, U., et al.: On achieving energy efficiency and reducing CO2 footprint in cloud computing. IEEE Trans. Cloud Comput. 4(2), 138–151 (2016)
Farahnakian, F. et al.: Using Ant colony system to consolidate VMs for green cloud computing. IEEE Trans. Serv. Comput. 8(2), 187–198 (2015)
Wang, Z., Yuan, Q.: A DVFS based energy-efficient tasks scheduling in a data center. IEEE Access 5, 13090–13102 (2017)
Singh, G, Mahajan, M.: VM Allocation in Cloud Computing Using SVM (2019). https://doi.org/10.35940/ijitee.I1123.0789S19
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Modh, R.M., Patel, M.B., Patel, J.N. (2022). An Extended Scheduling of Mobile Cloud using MBFD and SVM. In: Bhateja, V., Satapathy, S.C., Travieso-Gonzalez, C.M., Adilakshmi, T. (eds) Smart Intelligent Computing and Applications, Volume 1. Smart Innovation, Systems and Technologies, vol 282. Springer, Singapore. https://doi.org/10.1007/978-981-16-9669-5_41
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DOI: https://doi.org/10.1007/978-981-16-9669-5_41
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