Abstract
A host uses servers hired from a Cloud in order to offer certain services to paying customers. It must decide dynamically when and how many servers to hire, and when to release them, so as to minimize both the job holding costs and the server costs. Under certain assumptions, the problem can be formulated in terms of a semi-Markov decision process and the optimal hiring policy can be computed. Two situations are considered: (a) jobs are submitted in random batches and servers can be hired for arbitrary periods of time; (b) jobs arrive singly and servers must be hired for fixed periods of time. In both cases, the optimal policies are compared with some simple and easily implementable heuristics.
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References
Bennani, M.N., Menascé, D.: Resource allocation for autonomic data centers using analytic performance methods. In: Procs. 2nd IEEE Conf. on Autonomic Computing, ICAC 2005), pp. 229–240 (2005)
Bodík, P., Griffith, R., Sutton, C., Fox, A., Jordan, M., Patterson, D.: Statistical machine learning makes automatic control practical for internet datacenters. In: Conf. on Hot Topics in Cloud Computing, HotCloud 2009, Berkeley, CA, USA (2009)
Byun, E.-K., Kee, Y.-S., Kim, J.-S., Maeng, S.: Cost optimized provisioning of elastic resources for application workflows. Future Generation Computer Systems 27(8), 1011–1026 (2011), http://dx.doi.org/10.1016/j.future.2011.05.001
Byun, E.-K., Kee, Y.-S., Kim, J.-S., Deelman, E., Maeng, S.: BTS: Resource capacity estimate for time-targeted science workflows. Journal of Parallel and Distributed Computing 71(6), 848–862 (2011), doi:10.1016/j.jpdc.2011.01.008
Chandra, A., Gong, W., Shenoy, P.: Dynamic resourse allocation for shared data centers using online measurements. In: Procs. 11th ACM/IEEE Int. Workshop on Quality of Service (IWQoS), pp. 381–400 (2003)
Chaisiri, S., Lee, B.S., Niyato, D.: Optimization of resource provisioning cost in cloud computing. IEEE Transactions on Services Computing 5(2), 164–177 (2012)
Fox, B.L., Glynn, P.W.: Computing Poisson Probabilities. Management Science and Operations Research 31(4), 440–445 (1988)
Hiden, H., Woodman, S., Watson, P., Cala, J.: Developing cloud applications using the e-science central platform. Royal Soc. of London, Phil. Trans. A. (Mathematical, Physical and Engineering Science), 371 (2013)
Lampe, U., Siebenhaar, M., Hans, R., Schuller, D., Steinmetz, R.: Let the clouds compute: Cost-efficient workload distribution in infrastructure clouds. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds.) GECON 2012. LNCS, vol. 7714, pp. 91–101. Springer, Heidelberg (2012)
Mazzucco, M., Dyachuk, D., Dikaiakos, M.: Profit-aware server allocation for green internet services. In: IEEE Int. Symp. on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), pp. 277–284 (2010)
Mazzucco, M., Mitrani, I., Fisher, M., McKee, P.: Allocation and Admission Policies for Service Streams. In: Procs. MASCOTS 2008, Baltimore, pp. 155–162 (2008)
Mazzucco, M., Vasar, M., Dumas, M.: Squeezing out the cloud via profit-maximizing resource allocation policies. In: IEEE Int. Symp. on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), pp. 19–28 (2012)
Mitrani, I.: Managing Performance and Power Consumption in a Server Farm. Annals of Operations Research (2011), doi:10.1007/s10479-011-0932-1
Reibman, A., Trivedi, K.: Numerical transient analysis of Markov models. Computing and Operations Research 15(1), 19–36 (1988)
D. Thain, T. Tannenbaum and Miron Livny, “Distributed computing in practice: the Condor experience”, Concurrency and Computation: Practice and Experience, 17 (2-4),323-356, doi: http://dx.doi.org/10.1002/cpe.v17:2/4
Tijms, H.C.: Stochastic Models. John Wiley and sons (1994)
Urgaonkar, R., Kozat, U.C., Igarashi, K., Neely, M.J.: Dynamic Resource Allocation and Power Management in Virtualized Data Centers. In: IEEE/IFIP NOMS 2010, Osaka, Japan (2010)
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McGough, A.S., Mitrani, I. (2014). Optimal Hiring of Cloud Servers. In: Horváth, A., Wolter, K. (eds) Computer Performance Engineering. EPEW 2014. Lecture Notes in Computer Science, vol 8721. Springer, Cham. https://doi.org/10.1007/978-3-319-10885-8_1
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DOI: https://doi.org/10.1007/978-3-319-10885-8_1
Publisher Name: Springer, Cham
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