Storage area network management
Main Article Content
Abstract
The problems of effective management of tiered storage area network (SAN) are considered. The main independent variables and criteria for the operation SAN are defined. The criterion for selecting SAN management subsystem is proposed. The functional should covered with the SAN management subsystem is defined. Mathematical models for distribution users between SAN resources and management of tiered SAN resources are proposed. Genetic and heuristic algorithms for solving the problem of minimizing storage costs are proposed. The experimental results for different groups of tasks are given. It is shown that the genetic algorithm allows find a more effective solution than a heuristic algorithm. The average time spending on distribution of data depending on the dimension of the problem is estimated. The heuristic algorithm finds a solution faster than the genetic algorithm, but gives a less accurate result.
Reference 9, figures. 5, tables 1.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
Dubova N. (2005), “Business process management platforms.” Otkrytye sistemy. No.10. (Rus.)
Holland D. (1992), “Genetic algorithms”. V mire nauki. No.9 -10, Pp.32—40 (Rus.)
Orlov S. (2013), “SAN: unified and tiered storage” .LAN. Zhurnal setevyh reshenij. No.1 pp.38—40 (Rus.)
Pavlov O.A., Telenyk S.F. (2002), “Information technology and algorithmic in managing”. P. 344 (Ukr.)
State of the Data Center Survey: Global results. Symantec Corp. Sept. 2012. P. 12.
Telenyk S.F., Rolik A.I., Savchenko P.S., Bodaniuk M.E. (2011), “Controlled genetic algorithm for solving task of allocation virtual machines in data centers”. Visnyk ChDTU. No. 2., Pp.104—113 (Rus.)
Telenyk S.F., Rolik O.I., Bukasov M.M., Androsov S.A. (2010), “Genetic algorithms for solving re-source management data tasks in data centers”. Avtomatyka. Avtomatyzatsiia. Elektrotekhnichni kompleksi ta systemi. No.1 (25), Pp. 106—120 (Ukr.)
Telenyk S.F., Rolik O.I., Bukasov M.M., Sokolovskyi R.L. (2006), “Management system of corporate ICS”. Visnyk NTUU «KPI». Informatyka, upravlinnia ta obchysliuvalna tekhnika. K. «VEK+». No.45, Pp. 112—126 (Ukr.)
Zhukova S.A., Efimov I.N. (2007), “Corporate data storage optimization”. Mezhdunarodnyj zhurnal. Programmnye produkty i sistemy. No. 4. (Rus.)