Abstract
A multi-tenant database cluster is a concept of a data-storage subsystem for cloud applications with the multi-tenant architecture. The cluster is a set of relational database servers with the single entry point, combined into one unit with a cluster controller. This system is aimed to be used by applications developed according to Software as a Service (SaaS) paradigm and allows to place tenants at database servers so that it may provide their isolation, data backup and the most effective usage of available computational power. One of the most important problems on such a system is an effective distribution of data between servers, which affects the degree of individual cluster nodes load and fault-tolerance. This paper considers the data-management approach based on the usage of a load-balancing quality measure function. This function is used during the initial placement of new tenants and also during placement optimization steps. Standard schemes of metaheuristic optimization such as simulated annealing and tabu search are used to find a better tenant placement.
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References
Chong, F. and Carraro, G., Building Distributed Applications: Architecture Strategies for Catching the Long Tail Microsoft Development Network, 2006. http://msdn.microsoft.com/en-us/library/aa479069.aspx
Chong, F., Carraro, G., and Wolter, R., Multi-Tenant Data Architecture, Microsoft Corporation, 2006. http://msdn.microsoft.com/en-us/library/aa479086.aspx
Boytsov, E. and Sokolov, V., The problem of creating multi-tenant database clusters, Proc. SYRCoSE, Perm, 2012, pp. 172–177.
Boytsov, E.A., Designing and development of an imitation model of a multi-tenant database cluster, Model. Analis Inform. Sist., 2013, vol. 20, no. 4, pp. 136–149.
Boytsov, E. and Sokolov, V., The formal statement of the load-balancing problem for a multi-tenant database cluster, Proc. Spring/Summer Young Researchers’ Colloq. on Software Engineering, Kazan, 2013, pp. 117–121.
Boytsov, E. and Sokolov, V., Comparison of data management strategies for multi-tenant database cluster, Proc. Int. Symp. on Business Modeling and Software Design, Luxembourg, 2014, pp. 217–222.
Beckman, M. and Koopmans, T., Assignment problems and the location of economic activities, Econometrica, 1957, vol. 25, pp. 53–76.
Lee, C.-G. and Ma, Z., The Generalized Quadratic Assignment Problem, Tech. Rep. Univ. Toronto, Toronto, Canada: Department of Mechanical and Industrial Engineering, 2004.
Sahni, S. and Gonzalez, T., P-complete approximation problems, J. of ACM, 1976, vol. 23, pp. 555–565.
Burkard, R.E., Locations with spatial interactions: the quadratic assignment problem, in Discrete Location Theory, Mirchandani, P.B. and Francis, R.L., Eds., New York: Wiley, Ser. Discrete Math. Optim., 1990, pp. 387–437.
Rendl, F., Pardalos, P. and Wolkowicz, H., Proc DIMACS Workshop on Quadratic Assignment Problems, Am. Mathem. Soc., 1994, vol. 16, pp. 1–42.
Burkard, R.E. and Cela, E., Quadratic and three-dimensional assignment problems, in Annotated Bibliographies in Combinatorial Optimization, Dell’Amico, M., Maffioli, F., and Martello, S., Eds., Chichester: Wiley, 1997, pp. 373–392.
Holland, J.H., Adaptation in Natural and Artificial Systems, Cambridge: Mass. Inst. Technol., 1992.
Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P., Optimization by simulated annealing, Science. New Ser., 1983, vol. 220, pp. 671–680.
Glover, F., Future paths for integer programming and links to artificial intelligence, Compt. Oper. Res., 1986, vol. 13, pp. 533–549.
Elmore, A., Das, S., Agrawal, D., and El Abbadi, A., Zephyr: live migration in shared nothing databases for elastic cloud platforms, Proc. Int. Conf. on Management of Data, New York, 2011, pp. 301–312.
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Boytsov, E.A. Applying stochastic metaheuristics to the problem of data management in a multi-tenant database cluster. Aut. Control Comp. Sci. 48, 594–601 (2014). https://doi.org/10.3103/S0146411614070190
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DOI: https://doi.org/10.3103/S0146411614070190