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In the present work, we developed approaches for effective control of traffic flow in the virtual data center, based on the methods used in the data mining and machine learning to more accurately classify and identify streams of cloud-based applications and network services.
Nowadays the cloud computing technology is developing steadily and new approaches for work organization are still appearing. One of the problems of cloud computing technology is the control of the traffic in cloud applications and services in the network environment of virtual data center. The advantage of modern infrastructure's virtualization is the possibility to use the software-defined networks...
Data centers are widely used for the placement of highly loaded applications and solutions used to process large amounts of data (Big Data). The study developed a model of cloud application and services. The novelty of this model is the use of methods of intellectual analysis and prediction of dynamic characteristics in the study of multicomponent systems. In order to provide flexibility built models...
Data centers are widely used for the placement of highly loaded applications and solutions used for the processing of large data sets (BigData). For effective access to services, minimal response time of data storages is required. We explored a new paradigm in software-defined infrastructure distributed cloud systems. Also the design principles and high-level architectural design of the SD infrastructure...
Existing approaches to the use of computing resources is too wasteful for local date centers of educational institutions. Modern multimedia services require significant computing power, which are not always available. In this paper, we introduce an approach that allows more efficient use of limited resources by dynamically scheduling the distribution of data flows at several levels: between the physical...
This work proposes an approach to improve the effectiveness of access to multimedia learning resources of distance learning systems on the basis of the load balancing.
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