A huge pizza and a jug of water, why should 5G networks be sliced? The winners of RUDN science competition explain
Why are 3G and 4G not enough for us anymore?
Every year the number of devices that use mobile communications for work increases. The volume of files that need higher speeds to be transferred is also increasing. And mobile service providers need to provide them at affordable prices.
What are the advantages of 5G networks?
Their speed. The maximum download speed is 20 times faster compared to previous generations of networks. The delay between sending a request and receiving a response in 5G is 2 times shorter than, for example, in 4G.
Another feature of this generation of networks is Network Slicing. Thanks to this technology, we can divide one physical infrastructure into several virtual segments, each of which has its own dedicated resources.
For example?
Let's take radio frequencies. We have a giant pizza divided into several slices. Each slice with its own toppings for a certain guest, depending on their "food request". Police need one radio frequency, ambulances need a second, radio stations need a third. Slicing radio resources makes it possible to allocate certain parts of the network to specific tasks or users.
Or another example. A network without slicing radio resources is like a big water jug. When each person accesses it, they must share water with everyone else. This can lead to everyone getting only a small portion of water, and thus to a poor service. Now let's divide the contents of the jug into several containers, each for a specific person or group of people. Now everyone gets his or her own reserve of water. The division into containers is an example of slicing, through which it is possible to provide optimal service to each user.
And what does this have to do with 5G?
Imagine we have a cellular operator that provides its services to two types of users. Some of them actively use the resource during the day, while others use it at night. Hence, it follows that it is more appropriate for the operator to distribute its resources so that most of them are provided to the first user during the day and to the second user at night.
You investigated the allocation of resource management in 5G networks to improve their performance among mobile operators. What is the result of your project?
We have developed a model that optimally allocates resources in a 5G network between two virtual operators. A controlled mass service system differs from a simple mass service system by having a controller that signals and reallocates network resources between two virtual operators depending on the system state.
How was the research conducted?
Our model consisted of a network operator that provides resources and two virtual operators that provide services to users. To find the optimal resource reallocation policy, we applied Howard's integration algorithm. Numerical results showed that the optimal policy depends on several factors. There is the current state of the system and the weighting of our chosen principles, maximizing resource utilization while distributing them equally among users and tracking controller signals.
We found that the choice of initial allocation, which is based on one of the principles, plays an important role and choosing it correctly leads to a solution that is found in the minimum number of iterations - retries of an action. In our project we have also used single layer neural network to optimize resource management in 5G networks. Its advantage is its speed and ability to efficiently process large amounts of data.
The scientific director of the project is Irina Kochetkova, Candidate of Physical and Mathematical Sciences, Deputy Director of the Applied Mathematics & Communications Technology Institute of the Faculty of Physical, Mathematical and Natural Sciences, Associate Professor of the Probability Theory and Cyber Security Department of RUDN.
A Center for Green Diplomacy was created based on the RUDN Institute of Environmental Engineering. Among the goals is the integration of the results of scientific and practical activities into the development of international relations in the environmental sphere. The center's specialists will also accompany the corporate sector in solving various environmental problems.
The National Demographic Report, 2023 Demographic Well-Being of Russian Regions (hereinafter - the National Demographic Report) was prepared by the scientific team of the Institute of Demographic Studies of the Federal Research Center of the Russian Academy of Sciences, the Vologda Scientific Center of the Russian Academy of Sciences, Peoples' Friendship University of Russia, the Center for Family and Demography of the Academy of Sciences of the Republic of Tatarstan, as well as with the participation of leading scientists from the Republic of Bashkortostan, Stavropol Krai, Volgograd, Ivanovo, Kaliningrad, Nizhny Novgorod, Sverdlovsk Oblasts and Khanty-Mansi Autonomous Okrug–Yugra.
A Center for Green Diplomacy was created based on the RUDN Institute of Environmental Engineering. Among the goals is the integration of the results of scientific and practical activities into the development of international relations in the environmental sphere. The center's specialists will also accompany the corporate sector in solving various environmental problems.
What is your first association with the word “laboratory”? Flasks and beakers? Microscopes and centrifuges? Yes, many of us would answer the same way.
The National Demographic Report, 2023 Demographic Well-Being of Russian Regions (hereinafter - the National Demographic Report) was prepared by the scientific team of the Institute of Demographic Studies of the Federal Research Center of the Russian Academy of Sciences, the Vologda Scientific Center of the Russian Academy of Sciences, Peoples' Friendship University of Russia, the Center for Family and Demography of the Academy of Sciences of the Republic of Tatarstan, as well as with the participation of leading scientists from the Republic of Bashkortostan, Stavropol Krai, Volgograd, Ivanovo, Kaliningrad, Nizhny Novgorod, Sverdlovsk Oblasts and Khanty-Mansi Autonomous Okrug–Yugra.