Dynamic routing algorithms and methods for controlling traffic flows of cloud applications and services
Автор: Bolodurina I.P., Parfenov D.I.
Рубрика: Информатика, вычислительная техника и управление
Статья в выпуске: 2 т.6, 2017 года.
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Nowadays, we see a steady growth in the use of cloud computing in modern business. This enables to reduce the cost of IT infrastructure owning and operation; however, there are some issues related to the management of data processing centers. One of these issues is the effective use of companies' computing and network resources. The goal of optimization is to manage the traffic in cloud applications and services within data centers. Taking into account the multitier architecture of modern data centers, we need to pay a special attention to this task. The advantage of modern infrastructure virtualization is the possibility to use software-defined networks and software-defined data storages. However, the existing optimization of algorithmic solutions does not take into account the specific features of the network traffic formation with multiple application types. The task of optimizing traffic distribution for cloud applications and services can be solved by using software-defined infrastructure of virtual data centers. We have developed a simulation model for the traffic in software-defined networks segments of data centers involved in processing user requests to cloud application and services within a network environment. Our model enables to implement the traffic management algorithm of cloud applications and optimize the access to storage systems through the effective use of data transmission channels. During the experimental studies, we have found that the use of our algorithm enables to decrease the response time of cloud applications and services and, therefore, increase the productivity of user requests processing and reduce the number of refusals.
Software-defined network, data centers, cloud computing, it infrastructure
Короткий адрес: https://sciup.org/147160622
IDR: 147160622 | DOI: 10.14529/cmse170206
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