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News
May 14, 2026
Resource Race and Green Transition: Three Unexpected Conclusions from Foresight Centres Research on Climate and Poverty
Beneath the surface of green energy—which most people associate with solar panels, electric vehicles, and reduced CO2 emissions—lies a complex web of geopolitical interests, international inequality, and resource constraints. Researchers from the Laboratory for Science and Technology Studies (LST) at the HSE ISSEK Foresight Centre have published a series of articles in leading international journals on hidden and overt conflicts surrounding critically important metals and minerals, as well as related processes in the energy sector.
May 13, 2026
Immersion in Second Language Environment Influences Bilinguals Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
May 12, 2026
‘Any Real-Economy Company Can Use Our Products
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.

 

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Разработка моделей для расчета задержек доступа к контенту с учетом кеширования в сетях NDN

Информационно-управляющие системы. 2026. № 2. С. 36–48.
Iakimenko S.

Introduction: Caching reduces content access latency by bringing it closer to users and offloading the cloud layer of the network. Edge servers are used for this purpose, but the standard TCP/IP stack does not fully utilize caching capabilities. Therefore, it is necessary to consider a cache model using the Named Data Networking stack, which is more suited for this function. Purpose: To develop models for estimating content access latency, taking into account the specifics of caching at an intermediate node in NDN. Results: We propose a simulation model implementing the Least Recently Used caching algorithm based on discrete event modeling, as well as a mathematical model of delays in receiving content. These models allow for an adequate assessment of the latency on each segment from the user to the cloud, and for the system as a whole, and for calculating key cache performance characteristics: cache hit probability, load on external and internal channels. Edge server-based caching reduced content access latency to 65 ms, while reducing operator costs for accessing the remote cloud by up to 60%. Practical relevance: The results of this study can be used by internet service providers and telecom operators to reduce backbone bandwidth congestion and improve subscriber quality of service when downloading popular content. Discussion: The study used a scenario with a large catalog and a Poisson flow of edge cache requests, which corresponds to a regime in which the probability of request aggregation in the Pending Interest Table is low. Studying the dynamic effect of aggregation on content access latency requires a more complex traffic model (e.g., an ON-OFF or shot-noise model), which is the subject of further research.

Research target: Computer Science Electronics and Electrical Engineering
Language: Russian
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Keywords: имитационное моделированиеоблакоlatencysimulation modelingCloudзадержкаcachingEDGE CACHINGLeast Recently Usednon-zero download delayNamed Data NetworkingкешированиеLeast Recently Usednon-zero download delayграничное кешированиеNamed Data Networking
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