This article describes a cloud educational resource datacenter (CERD) as the means of providing an economically profitable remote access to paid and free software for educational facilities. The problem of efficient CERD scheduling for optimizing the use of cloud virtual machines and software licenses have been studied in details. We have implemented two evolutionary algorithms: simulated annealing and genetic algorithm for this problem. The simulation model of CERD is presented. The UML class diagram of CERD simulator is described. The algorithm estimation criteria are the performance time and the count of satisfied requests. The simulated annealing algorithm showed the best results by all criteria.
Shukhman, A., Bolodurina, I., Polezhaev, P., & Legashev, L. (2017). Cloud Educational Resource Datacenter Simulator. In Procedia Computer Science (Vol. 103, pp. 543–548). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.01.052