Operation of Cellular Networks Found Similar to Bacteria Growth in Petri Dish
Scientists at HSE University have discovered an approach to analysing mobile communication quality by applying the principles of surface physics
Scientists at the HSE Laboratory for Computational Physics have developed a new model for analysing communication networks that can significantly enhance the speed of mobile communications. To achieve this, the researchers used computational physics methods and phase transition models. It turns out that the functioning of cellular networks is in many ways similar to the growth of surfaces in physics. The study was performed using the HPC cHARISMa cluster at HSE University. The study findings have been published in Frontiers in Physics.
Mobile networks enable making calls, sending messages, and using the internet. However, for these networks to function smoothly, it is essential to be able to simulate their operation. Simulations help predict how a network will behave in various situations, including extreme conditions, and identify areas for improvement.
One of the key tools for studying mobile networks is parallel discrete-event simulation (PDES). This method is based on splitting a system into numerous subsystems to enable parallel modelling of various processes. Each of these subsystems has its own local virtual time, which does not align with the actual time. When the local times significantly diverge from each other, leading to process desynchronisation, the network may experience slower operation or errors. Lev Shchur and Liliia Zhukova, scientists at HSE MIEM, studied the evolution of local virtual time profiles in a cellular communication model and discovered similarities with the surface growth processes in physics.
Associate Professor, School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics
After conducting a thorough analysis of the processes, we observed similarities between changes in local time in cellular communication modelling and alterations in a surface profile as it grows, eg through spray application, as the time only progresses forward. Surface physics is a well-established field with equations that facilitate analysis and modelling of various processes. We have transferred knowledge from this domain to computing technologies and constructed a model simulating the evolution of local virtual time profiles.
By comparing their findings with a model of a real mobile network, the scientists have found that the proposed method enables accurate prediction of critical moments when the network's performance may deteriorate, so that issues can be addressed proactively, leading to improved network operation.
Head, Laboratory for Computational Physics, HSE Tikhonov Moscow Institute of Electronics and Mathematics
With the help of computational physics algorithms, it becomes possible to determine the moment when local time ceases to progress, referred to in physics as the phase transition point. We can describe the events occurring around it and anticipate potential communication disruptions or alterations in load distribution at a cellular communication station. With this model, we can provide the industry with better tools for planning, constructing, and operating mobile networks.
The researchers emphasise that understanding the mechanics of parallel computing in actual high-load networks will facilitate faster and more efficient simulation of mobile networks and other systems employing similar calculations across various domains such as engineering, computer science, economics, and transportation.
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