Abstract
The boom of Mobile Cloud Computing fosters a large volume of smart mobile applications enabling processing and data handlings in the remote cloud servers. An Efficient allocation of resources to a large number of requests in Mobile Cloud Computing environment is an important aspect that needs special attention in order to make the environment a highly optimized entity. In this paper, A Cuckoo based allocation strategy is proposed and the allocation is considered as an optimization problem with the aim of reducing the makespan and the computational cost meeting the deadline constraints, with high resource utilization. The proposed approach is evaluated using CloudSim framework and the results, indicate that the proposed model provides better quality of service to the mobile cloud customers.
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References
Dinh, H.T., Lee, C., Nyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications and approaches. Wirel. Commun. Mob. Comput. 13, 1587–1611 (2013)
Escalnte, D., Andrew, J.: Cloud services: policy and assessment. Educause Rev. 46 (2011)
Shiraz, M., Gani, A., Khokhar, R.H., Buyya, R.: A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. IEEE Commun. Surv. 15, 1294–1313 (2013)
Pandey, S., Wu, L., Guru, S.M., Buyya, R.: A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments. In: Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications (AINA) (2010)
Sandeep, K., Sandhu, R.: Matrix based proactive resource provisioning in mobile cloud environment. Elsevier. J. Simul. Model. Pract. Theory 50, 83–95 (2015)
Nishio, T., Shinkuma, R., Takahashi, T., Narayan, B.: Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud. In: Mobile Cloud ’13, Proceedings of the First International Workshop on Mobile Cloud Computing and Networking, pp. 19–26 (2013)
Ravi, A., Peddoju, S.K.: Energy efficient seamless service provisioning in mobile cloud computing, In: Proceedings of the 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering. pp. 463–471 (2013)
Shu, W., Wang, W., Wang, Y.: A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing. EURASIP J. Wirel. Commun. Netw. 64 (2014)
Yang, X.S., Deb, S.: Cuckoo search via levy flights. In: World Congress Nature and Biologically Inspired Computing, pp. 210–214 (2009)
Yang, X.S., Deb, S.: Engineering optimization by cuckoo search. Int. J. Math. Model. Numer. Optim. 1, 330–343 (2010)
Civicioglu, P., Besdok, E.: A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Artif. Intell. Rev. 39, 315–346 (2013)
Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, A.F., Buyya, R.: CloudSim: a toolkit for modelling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw.: Pract. Experience 41, 23–50 (2011)
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Durga, S., Mohan, S., Dinesh, J., Aneena, A. (2016). Cuckoo Based Resource Allocation for Mobile Cloud Environments. In: Senthilkumar, M., Ramasamy, V., Sheen, S., Veeramani, C., Bonato, A., Batten, L. (eds) Computational Intelligence, Cyber Security and Computational Models. Advances in Intelligent Systems and Computing, vol 412. Springer, Singapore. https://doi.org/10.1007/978-981-10-0251-9_50
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DOI: https://doi.org/10.1007/978-981-10-0251-9_50
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