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21st Conference on Scientific Services and Internet, SSI 2019

作者： Lavrischeva, E.M. Petrenko, A.K. Pozin, B.A. Ivannikov Institute for System Programming of the Russian Academy of Sciences 25 Alexander Solzhenitsyn st. Moscow109004 Russia Moscow Institute of physics and technology 9 Institutsky per. Dolgoprudny Moscow region141700 Russia NRU Higher School of Economics 20 Myasnitskaya Ulitsa Moscow101000 Russia Lomonosov Moscow State University GSP-1 Leninskie Gory Moscow119991 Russia EC-leasing Building 1 125 Warshavskoye Shosse Moscow117587 Russia

The technology of Assembly of intellectual (Reuses) and information (data) resources which are developed and saved up in libraries and storages of the Internet, in applied web-systems of different function is offered. The intellectual tasks of subject areas of knowledge in the Semantic Web in mind service, software and system resources used in creating Web systems are presented. Methods of assembling resources (link, make, assemble, weaver, kconfig) are considered for modern environments. The problem of data exchange and generation to the formats of the global network environment according to ISO/IEC 11404 GDT is defined. The concept of a network resource collector is proposed as a generalization of ways to assemble resources with functional security, resource protection and quality assessment of Web-systems. Perspective paradigms of programming of different areas of knowledge are defined. Copyright © 2020 for this paper by its authors.

关键词： Web services

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Optics in Computer Architectures: Basis of WDM, Technologies and Potentials

Optics in Computer Architectures: Basis of WDM, Technologies...

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ICONS International Conference on systems

作者： Y. Wang T. Kusserrow S. Irmer A. Hasse M. Bartels N. Dharmarasu H. Hillmer J. Borcsok O. Mikami Institute of Nanostructure Technologies and Analytics (INA) University of Kassel Kassel Germany Department of Computer Architecture and System Programming University of Kassel Germany Department of Information Telecommunication and Electronics Tokai University Hiratsuka-shi Japan

We present novel concepts, technologies and potentials of optical data communication, especially for future computer architectures. The WDM (wavelength division multiplexing) and the optical wiring technologies are explained in detail. Experimental results of tunable optical filters, which play a major role in WDM systems, are reported. New concepts for novel optical interconnectors and novel miniaturized lasers for direct generation of green light are proposed as examples for possible next generation components to improve the performance of optical communication based computer architecture.

关键词： Optical computing Computer architecture Wavelength division multiplexing Optical filters Optical interconnections Data communication Wiring Tunable circuits and devices Optical devices Optical fiber communication

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Sensing Metric-Based Hybrid Underlay/Overlay Transmission Framework for CR-IoT Networks for Smart City Applications 7

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Fr...

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7th IET Smart Cities Symposium, SCS 2023

作者： Bala, Indu Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results. © The Institution of Engineering & Technology 2023.

关键词： Smart city

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Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula 24

Applying language models to algebraic topology: generating s...

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Proceedings of the 41st International Conference on Machine Learning

作者： Kirill Brilliantov Fedor Pavutnitskiy Dmitry Pasechnyuk German Magai ETH Zurich Beijing Institute of Mathematical Sciences and Applications Beijing Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi and Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow HSE University Moscow and Noeon Research Tokyo

Computing homotopy groups of spheres has long been a fundamental objective in algebraic topology. Various theoretical and algorithmic approaches have been developed to tackle this problem. In this paper we take a step towards the goal of comprehending the group-theoretic structure of the generators of these homotopy groups by leveraging the power of machine learning. Specifically, in the simplicial group setting of Wu's formula, we reformulate the problem of generating simplicial cycles as a problem of sampling from the intersection of algorithmic datasets related to Dyck languages. We present and evaluate language modelling approaches that employ multilabel information for input sequences, along with the necessary group-theoretic toolkit and nonneural baselines.

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Decentralized Personalized Federated Learning for Min-Max Problems

arXiv

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arXiv 2021年

作者： Borodich, Ekaterina Beznosikov, Aleksandr Sadiev, Abdurakhmon Sushko, Vadim Savelyev, Nikolay Takac, Martin Gasnikov, Alexander Moscow Institute of Physics and Technology Moscow Russia Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates Ivannikov Institute for System Programming RAS Moscow Russia Bosch Center for Artificial Intelligence Renningen Germany

Personalized Federated Learning (PFL) has witnessed remarkable advancements, enabling the development of innovative machine learning applications that preserve the privacy of training data. However, existing theoretical research in this field has primarily focused on distributed optimization for minimization problems. This paper is the first to study PFL for saddle point problems encompassing a broader range of optimization problems, that require more than just solving minimization problems. In this work, we consider a recently proposed PFL setting with the mixing objective function, an approach combining the learning of a global model together with locally distributed learners. Unlike most previous work, which considered only the centralized setting, we work in a more general and decentralized setup that allows us to design and analyze more practical and federated ways to connect devices to the network. We proposed new algorithms to address this problem and provide a theoretical analysis of the smooth (strongly) convex–(strongly) concave saddle point problems in stochastic and deterministic cases. Numerical experiments for bilinear problems and neural networks with adversarial noise demonstrate the effectiveness of the proposed methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Numerical methods

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Reproducing Network Structure: A Comparative Study of Random Graph Generators

Reproducing Network Structure: A Comparative Study of Random...

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Ivannikov ISPRAS Open Conference (ISPRAS)

作者： Mikhail Drobyshevskiy Denis Turdakov Sergey Kuznetsov Moscow Institute of Physics and Technology (State University) Moscow Russia Russian Academy of Sciences Ivannikov Institute for System Programming Moscow Russia National Research University Higher School of Economics Moscow Russia Lomonosov Moscow State University Moscow Russia

The problem of generating graphs similar to a given one arises in such tasks as data anonymization and significance testing of network mining tools. Main challenges lie in a rich diversity of graph domains emerging in various research areas and the uncertainty about graph properties to be reproduced. Our central statement is that a good graph generation model should follow two requirements on generated graphs: 1) similarity to the original one in terms of manifold graph metrics, and 2) variability wide enough to mimic natural diversity across a graph domain. In this work we have compared three state-of-the-art graph generators, Embedding based Random Graph Generator, Gscaler, and Stochastic Kronecker Graph, universal enough to fit an arbitrary graph. We found that ERGG and Gscaler greatly outperform SKG in graph reproducing accuracy in terms of graph metrics. An experiment with domain imitation showed that the variability of ERGG generated graphs resembled the original variability, while Gscaler graphs were almost identical.

关键词： Measurement Adaptation models Social network services Computational modeling Generators Task analysis Testing

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Multi-Agent Approach for Dynamic Elasticity of Virtual Machines Provisioning in Heterogeneous Distributed Computing Environment

Multi-Agent Approach for Dynamic Elasticity of Virtual Machi...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Alexander Feoktistov Ivan Sidorov Andrei Tchernykh Alexei Edelev Valery Zorkalzev Roman Kostromin Sergey Gorsky Igor Bychkov Arutyun Avetisyan Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia Matrosov Inst. for Syst. Dynamics & Control Theor. Irkutsk Russia Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia Melentiev Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia

ISBN: (纸本)9781538678800

We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated resources (private cloud) for providing virtualized service and non-dedicated resources for Grid-computing. Existing platforms for the resource virtualization does not support management of such an infrastructure. We propose an approach to a job management based on the dynamic elasticity of virtual machines provisioning using resources of both types. We develop the multi¬agent job scheduler for dedicated resources and hypervisor shell to launch virtual machines through queues of resource management systems in non-dedicated resources. The scheduler provides a dynamic elasticity of virtual machine provisioning. Advantages of the offered approach to the resource virtualization are demonstrated by an example of a job flow management for a scalable application to solve the complicated practical problem. It is related to the energy security of Vietnam. Provided experiments show that using the developed tools together with the platform for the resource virtualization enables agents to significantly speed up the problem-solving process.

关键词： Cloud computing Resource management Dynamic scheduling Virtual machine monitors Elasticity Virtual machining

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Scale effects in internal wave attractors

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Physical Review Fluids 2017年第11期2卷 114803-114803页

作者： C. Brouzet I. N. Sibgatullin E. V. Ermanyuk S. Joubaud T. Dauxois Université de Lyon ENS de Lyon Université Claude Bernard CNRS Laboratoire de Physique F-69342 Lyon France Moscow State University 119991 Moscow Russia Institute for System Programming 109004 Moscow Russia Shirshov Institute of Oceanology 117997 Moscow Russia Lavrentyev Institute of Hydrodynamics Novosibirsk 630090 Russia Novosibirsk State University Novosibirsk 630090 Russia

As a necessary preliminary step toward geophysically significant extrapolations, we study the scale effects in internal wave attractors in the linear and nonlinear regimes. We use two geometrically similar experimental setups, scaled to factor 3, and numerical simulations (a spectral element method, based on the Nek5000 open solver) for a range of parameters that is typically accessible in laboratory. In the linear regime, we recover the classical viscous scaling for the beam width, which is not affected by variations of the amplitude of the input perturbation. In the nonlinear regime, we show that the scaling of the width-to-length ratio of the attractor branches is intimately related with the energy cascade from large-scale energy input to dissipation. We present results for the wavelength, amplitude, and width of the beam as a function of time and as a function of the amplitude of the forcing.

关键词： Flow instability Geophysical fluid dynamics Stratified geophysical flows Hydrodynamic waves

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Min-max optimization over slowly time-varying graphs

arXiv

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arXiv 2023年

作者： Nguyen, Nhat Trung Rogozin, Alexander Metelev, Dmitriy Gasnikov, Alexander Moscow Institute of Physics and Technology Moscow Russia Institute for Information Transportation Problems Moscow Russia Caucasus Mathematic Center Adygh State University Moscow Russia Ivannikov Institute for System Programming The Russian Academy of Sciences Research Center for Trusted Artificial Intelligence Moscow Russia

Distributed optimization is an important direction of research in modern optimization theory. Its applications include large scale machine learning, distributed signal processing and many others. The paper studies decentralized min-max optimization for saddle point problems. Saddle point problems arise in training adversarial networks and in robust machine learning. The focus of the work is optimization over (slowly) time-varying networks. The topology of the network changes from time to time, and the velocity of changes is limited. We show that, analogically to decentralized optimization, it is sufficient to change only two edges per iteration in order to slow down convergence to the arbitrary time-varying case. At the same time, we investigate several classes of time-varying graphs for which the communication complexity can be reduced. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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DECENTRALIZED FINITE-SUM OPTIMIZATION OVER TIME-VARYING NETWORKS

arXiv

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arXiv 2024年

作者： Metelev, Dmitry Chezhegov, Savelii Rogozin, Alexander Beznosikov, Aleksandr Sholokhov, Alexander Gasnikov, Alexander Kovalev, Dmitry Moscow Institute of Physics and Technology Moscow Russia The National Research University Higher School of Economics Moscow Russia University Innopolis Innopolis Russia Ivannikov Institute for System Programming Russian Academy of Sciences Moscow Russia Yandex Research Moscow Russia

We consider decentralized time-varying stochastic optimization problems where each of the functions held by the nodes has a finite sum structure. Such problems can be efficiently solved using variance reduction techniques. Our aim is to explore the lower complexity bounds (for communication and number of stochastic oracle calls) and find optimal algorithms. The paper studies strongly convex and nonconvex scenarios. To the best of our knowledge, variance reduced schemes and lower bounds for time-varying graphs have not been studied in the literature. For nonconvex objectives, we obtain lower bounds and develop an optimal method GT-PAGE. For strongly convex objectives, we propose the first decentralized time-varying variance-reduction method ADOM+VR and establish lower bound in this scenario, highlighting the open question of matching the algorithms complexity and lower bounds even in static network case. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

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