Abstract
Heterogeneous clouds are helpful for improving performance when the data processing task becomes a challenge in big data within different operating environment. Non-distributive manner has some limitation, such as overload energy and low performance resource allocation mechanism. This paper address on this issue and propose an approach to find out the optimal data allocation plan for minimizing total costs of the distributed heterogeneous cloud memories in mobile cloud systems. In this paper, we propose a novel approach to find out the optimal data allocation plan to reduce data processing cost through heterogeneous cloud memories for efficient MaaS. The experimental results proved that our approach is an effective mechanism.
This work is supported by National Natural Science Foundation of China (No. U1304615) and the Science and Technology Research Key Project of Henan Province Science and Technology Department (No.162102210172).
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References
Hao, F., Min, G., Chen, J., Wang, F., Lin, M., Luo, C., Yang, L.: An optimized computational model for multi-community-cloud social collaboration. IEEE Trans. Serv. Comput. 7(3), 346–358 (2014)
Basu, A., Gandhi, J., Chang, J., Hill, M., Swift, M.: Efficient virtual memory for big memory servers. In: ACM SIGARCH Computer Architecture News, vol. 41, pp. 237–248. ACM (2013)
Wei, Z., Pierre, G., Chi, C.: Cloudtps: Scalable transactions for web applications in the cloud. IEEE Trans. Serv. Comput. 5(4), 525–539 (2012)
Qiu, M., Chen, L., Zhu, Y., Hu, J., Qin, X.: Online data allocation for hybrid memories on embedded tele-health systems. In: 2014 IEEE International Conference on High Performance Computing and Communications, 2014 IEEE 6th International Symposium on Cyberspace Safety and Security, 2014 IEEE 11th International Conference on Embedded Software and System, pp. 574–579. IEEE (2014)
Mao, H., Xiao, N., Shi, W., Lu, Y.: Wukong: a cloud-oriented file service for mobile internet devices. J. Parallel Distrib. Comput. 72(2), 171–184 (2012)
Katsalis, K., Sourlas, V., Korakis, T., Tassiulas, L.: A cloud-based content replication framework over multi-domain environments. In: 2014 IEEE International Conference on Communications (ICC), pp. 2926–2931. IEEE (2014)
Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for vm-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009)
Chen, M., Zhang, Y., Li, Y., Mao, S., Leung, V.: EMC: emotion-aware mobile cloud computing in 5G. IEEE Network 29(2), 32–38 (2015)
Liang, H., Cai, L., Huang, D., Shen, X., Peng, D.: An smdp-based service model for interdomain resource allocation in mobile cloud networks. IEEE Trans. Veh. Technol. 61(5), 2222–2232 (2012)
Sood, S., Sandhu, R.: Matrix based proactive resource provisioning in mobile cloud environment. Simul. Model. Pract. Theory 50, 83–95 (2015)
Qiu, M., Chen, Z., Ming, Z., Qin, X., Niu, J.: Energy-aware data allocation with hybrid memory for mobile cloud systems. IEEE Syst. J. 99, 1–10 (2014)
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Zhao, H., Qiu, M., Gai, K., Li, J., He, X. (2017). Cost Reduction for Data Allocation in Heterogenous Cloud Computing Using Dynamic Programming. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2016. Lecture Notes in Computer Science(), vol 10135. Springer, Cham. https://doi.org/10.1007/978-3-319-52015-5_1
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DOI: https://doi.org/10.1007/978-3-319-52015-5_1
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