Abstract
Cloud computing is becoming more and more popular and attracts considerable attention. In the there-tire cloud environment, an important problem is to determine the optimal multi-server system configuration so that the profit of the service provider can be maximized. In related work, the maximum allowed waiting time of service is assumed to be a constant, and the rental price is also assumed to be constant for all servers despite the fact that different servers have different execution speeds. These assumptions may not be valid in realistic cloud environments. In this paper, we propose an optimization model to determine the optimal configuration of the multi-server system. There are two major differences of the proposed model with that of the existing work. First, the maximum allowed waiting time is not a constant and may change with different service requests. Second, the situation that the servers with different execution speed may have different rental prices is taken into account. Experiments are carried out to verify the performance of the proposed optimization model. The results show that the proposed optimization model can help the service provider gain more profit than the existing work.
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References
Lee, Y.C., Wang, C., Zomaya, A.Y., Zhou, B.B.: Profit-driven service request scheduling in clouds. In: Proceedings of the 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 15–24 (2010)
Chen, J., Wang, C., Zhou, B.B., Sun, L., Lee, Y.C., Zomaya, A.Y.: Tradeoffs between profit and customer satisfaction for service provisioning in the cloud. In: Proceedings of the 20th International Symposium on High Performance Distributed Computing, pp. 229–238. ACM (2011)
Cao, J., Hwang, K., Li, K., Zomaya, A.Y.: Optimal multiserver configuration for profit maximization in cloud computing. IEEE Trans. Parallel Distrib. Syst. 24(6), 1087–1096 (2013)
Mei, J., Li, K., Ouyang, A., Li, K.: A profit maximization scheme with guaranteed quality of service in cloud computing. IEEE Trans. Comput. 64(11), 3064–3078 (2015)
Li, K., Mei, J., Li, K.: A fund-constrained investment scheme for profit maximization in cloud computing. IEEE Trans. Serv. Comput. (2016). IEEE Early Access Articles
Ghamkhari, M., Mohsenian-Rad, H.: Energy and performance management of green data centers: a profit maximization approach. IEEE Trans. Smart Grid 4(2), 1017–1025 (2013)
Liu, Z., Wang, S., Sun, Q., Zou, H., Yang, F.: Cost-aware cloud service request scheduling for SaaS providers. Comput. J. 57, 291–301 (2013)
de Langen, P., Juurlink, B.: Leakage-aware multiprocessor scheduling. J. Sig. Process. Syst. 57(1), 73–88 (2009)
Mei, J., Li, K., Hu, J., Yin, S., Sha, E.H.-M.: Energy-aware preemptive scheduling algorithm for sporadic tasks on DVS platform. Microprocess. Microsyst. 37(1), 99–112 (2013)
Ross, S.M.: Introduction to Probability Models, 11th edn. Elsevier, London (2014)
Boots, N.K., Tijms, H.: An M/M/c queue with impatient customers. Top 7(2), 213–220 (1999)
Ding, Y., Qin, X., Liu, L., Wang, T.: Energy efficient scheduling of virtual machines in cloud with deadline constraint. Future Gener. Comput. Syst. 50, 62–74 (2015)
Enhanced Intel® SpeedStep® technology for the Intel® Pentium® M processor. White Paper, Intel, March 2004
Li, K.: Optimal configuration of a multicore server processor for managing the power and performance tradeoff. J. Supercomput. 61(1), 189–214 (2012)
Chen, J., Wang, C., Zhou, B.B., Lee, Y.C., Zomaya, A.Y.: Tradeoffs between profit and customer satisfaction for service provisioning in the cloud (2011)
https://en.wikipedia.org/wiki/Stirling’s_approximation (2016)
Ghamkhari, M., Mohsenian-Rad, H.: Energy and performance management of green data centers: a profit maximization approach. IEEE Trans. Smart Grid 4(2), 1017–1025 (2013)
Li, K., Liu, C., Zomaya, A.Y.: A framework of price bidding configurations for resource usage in cloud computing. IEEE Trans. Parallel Distrib. Syst. 27(8), 2168–2181 (2016)
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This work is supported by Sichuan Provincial Project of International Scientific and Technical Exchange and Research Collaboration Programs (Project No. 2016HH0023).
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Kang, Z., Yang, B. (2018). A Study of Optimal Multi-server System Configuration with Variate Deadlines and Rental Prices in Cloud Computing. In: Zu, Q., Hu, B. (eds) Human Centered Computing. HCC 2017. Lecture Notes in Computer Science(), vol 10745. Springer, Cham. https://doi.org/10.1007/978-3-319-74521-3_25
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DOI: https://doi.org/10.1007/978-3-319-74521-3_25
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