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Восков Леонид Сергеевич

Московский институт электроники и математики им. А.Н. Тихонова

Профиль на hse.ru ↗ тел.: +7 (495) 772-95-90 | 15114 | +7 (910) 401-35-71
Публикаций
64
Языков
1
Наград
14
Конференций
0
Профиль Публикации (64) Курсы (3)

Профессиональные интересы

20.00.00 Информатика28.00.00 Кибернетика47.00.00 Электроника. Радиотехника49.00.00 Связь50.00.00 Автоматика. Вычислительная техника

Должности

  • Профессор — Московский институт электроники и математики им. А.Н. Тихонова, Департамент компьютерной инженерии

Био

  • · Начал работать в НИУ ВШЭ в 2009 году.
  • · Научно-педагогический стаж: 51 год.

Образование

  • 1983 · Ученое звание: Доцент
  • 1974 · Кандидат наук: Московский институт электронного машиностроения, специальность 05.13.12 «Системы автоматизации проектирования»
  • 1974 · Аспирантура: Московский институт электронного машиностроения, факультет: Автоматики и вычислительной техники, специальность «05.13.12. Системы автоматизации проектирования»
  • 1968 · Специалитет: Московский институт электронного машиностроения, факультет: Автоматики и вычислительной техники, специальность «Математические и счетно-решающие приборы и устройства», квалификация «Инженер-электрик»

Опыт работы

  • · 2009: Начал работать в НИУ ВШЭ в году, научно-педагогический стаж: 50 лет
  • · 1968-2009 г: г. - Московский институт электроники и математики::инженер исследователь, начальник смены ЭВМ, аспирант, стажер-исследователь Эдинбургского университета (Великобритания, Лаборатории искусственного интеллекта), м.н.с, ассистент, старший преподаватель, доцент, профессор кафедры "Вычислительные системы и сети"
  • · 2009г.–2025 г: г. - Московский институт электроники и математики им. А.Н.Тихонова НИУ ВШЭ: Старший научный сотрудник Научная лаборатория Интернета вещей и киберфизических систем, профессор-исследователь департамента компьютерной инженерии, научный руководитель образовательной программы: Интернет вещей и киберфизические системы
  • · 2020: Восков_резюме (PDF, 168 Кб)

Награды и поощрения

  • · Лауреат премии "Золотая вышка" - 2015 Представление Церемония Фото Благодарность Министерства образования и науки РФ 2012-04-09 Медаль "В память 850-летия Москвы" 1997-02-20
  • · Медаль "Признание - 10 лет успешной работы" НИУ ВШЭ (июль 2025)
  • · Благодарность НИУ ВШЭ (апрель 2025)
  • · Благодарственное письмо проректора НИУ ВШЭ (май 2020)
  • · Благодарность проректора НИУ ВШЭ (февраль 2019)
  • · Благодарность Высшей школы экономики (ноябрь 2013)
  • · Благодарность Высшей школы экономики (август 2013)
  • · Надбавка за академические успехи и вклад в научную репутацию НИУ ВШЭ (2023)
  • · Надбавка за академические успехи и вклад в репутацию НИУ ВШЭ (2012–2014)
  • · Надбавка за академическую работу (2017–2018, 2016–2017, 2015–2016, 2014–2015)
  • · Надбавка за публикацию в журнале из Списка А (и приравненном к нему научном издании) (2023–2024)
  • · Надбавка за публикацию в международном рецензируемом научном издании (2021–2022, 2020–2022)
  • · Лучший преподаватель — 2024–2025, 2013–2020
  • · Лауреат премии "Золотая Вышка" 2015 в номинации Достижения в преподавательской деятельности

Гранты и проекты

  • 2015 · Научный руководитель НУГ «Теоретические основы беспроводных сенсорных сетей» 2014, 2015 г.г., (заявка №14-05-0064)
  • 2017 · Научный руководитель НУГ "Разработка основ теории энергоэффективного взаимодействия ограниченных в ресурсах автономных устройств в рамках парадигмы интернета вещей" 2017г. (заявка № 17-05-0017)
  • 2019 · Научный руководитель НУГ «Энергоэффективное взаимодействие интернета удаленных вещей и киберфизических систем в условиях неразвитой сетевой инфраструктуры». 2019 г. (заявка №19-04-022).
  • 2023 · Научный руководитель НУГ "«Исследование методов преодоления ограничений взаимодействия киберфизических систем в гетерогенных сетях удаленного интернета вещей» 2023 г. (заявка №23-00-035)

Идентификаторы исследователя

Публикации (64)

Data Compression Strategies for Enhancing IoRT Communications over Heterogeneous Terrestrial-Satellite Networks

2023 · CHAPTER · en

Data transmission over low-speed networks is a subject of global research interest, with a specific focus on overcoming limitations in satellite communication channels. However, little research has addressed the impact of compression on data transmission efficiency in heterogeneous networks using satellite links, especially in the context of the Internet of Remote Things and under poor terrestrial network infrastructure. This study explores various data compression algorithms customized for tiny data in such scenarios. It identifies effective algorithms when combined with ProtoBuf serialization, achieving compression ratios between 3.5 and 8.2 for JSON messages of 30 to 680 bytes using the Huffman algorithm with an extended dictionary. For messages sized 680 to 2,048 bytes, Protobuf combined with LZ78 achieves compression ratios of 3.5 to 4.5. Moreover, a novel data preprocessing method is introduced, boosting processing performance by up to 27 times for messages under 680 bytes in size. These findings contribute to IoRT data serialization and compression and can potentially enhance existing methods.

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Experimental LoRa Network Power Consumption Model Using Multi-Hops

2022 · CHAPTER · en

The article describes the study of data transmission methods in heterogeneous networks using LoRa relay and NB-IoT gateway for use in an underdeveloped or absent Internet network infrastructure. The analysis of the subject area is carried out, a multistage architecture of a heterogeneous network of the Internet of Things is proposed, using repeaters and a gateway to collect remote data. A method and a calculation model of energy consumption for the transmission of collected data using repeaters is proposed, which makes it possible to increase the energy efficiency of data transmission from end devices using autonomous powersources. A prototype of a data acquisition system withretransmission has been developed, which confirms the theoretical calculations. The practical value lies in increasing thebattery life and expanding the network coverage area. © 2022 IEEE.

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The study of Machine Learning Scenarios for the Internet of Arctic Things

2022 · CHAPTER · en

The paper investigated the problem of using IoT data transmission technologies in the absence or underdeveloped network infrastructure. As a result of a study of the technologies used in the IoT for data transmission, the LoRaWAN data transmission network was selected. A model of the functioning of IoT devices of a sensor network and a method for increasing the efficiency of data transmission using machine learning methods on terminal data collection devices to reduce the amount of transmitted data and increase the energy efficiency of systems are proposed. The proposed method was evaluated. The proposed method of using machine learning methods significantly increases the lifetime of terminal devices with certain strategies for collecting and processing data. The method allows to increase the maximum number of simultaneously connected devices, by reducing the use of the radio channel, since only processed information is sent. Processing data on edge devices using machine learning methods increases the autonomy of the IoT system, thereby increasing its reliability and providing increased data protection. With the development of computing systems, the use of machine learning on terminal devices will become more widespread. © 2022 IEEE.

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Обзор методов моделирования нательной связи

2022 · ARTICLE · ru

Беспроводные нательные сети обеспечивают энергоэффективную передачу данных между носимыми устройствами. Нательная связь является одной из технологий, используемых беспроводными нательными сетями. Данные передаются по телу человека, состоящему из разных тканей тела. При разработке устройств, использующих нательные сети, требуется моделирование передачи сигнала по тканям тела. В статье представлен обзор по моделированию нательной связи в многослойной среде тканей тела человека. В работе исследованы, классифицированы методы моделирования передачи сигнала по тканям тела и дана их оценка. Рассмотрены проблемы разработки, моделирования нательных сетей и основные требования к их проектированию.

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A survey on energy efficiency intrabody communication techniques for wearable devices

2021 · ARTICLE · en

Currently, wireless body area networks (WBANs) are developing rapidly. Miniature wearable devices which are light weight and low power consumption can be developed using modern technology. However, the WBANs research challenge is power consumption. This paper provides the two intrabody communication (IBC) methods review. The equivalent body channel models and modeling methods are analyzed. The conventional IBC WBANs architecture is reviewed and novel energy-efficient architecture and an IBC WBANs data transmission technique are proposed. The experiment was conducted in order to measure the BodyCom mobile module output power. The comparative analysis showed that the power consumption of the IBC proposed technique is 7 times lower than Bluetooth LE, and 14 times lower than ZigBee. The proposed technique can be applied in areas such as home and industrial automation, medical appliances, wearable devices, security, and internet of things.

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Gateway Data Encoding, Packaging and Compression method for heterogeneous IoT-satellite network

2021 · CHAPTER · en

Reducing the cost of data transmission is actively pursued all over the world. A separate direction in this area is the study of possibilities to reduce the cost of transmission of messages via a satellite communication channel. However, studies of the possibility of reducing the cost of message transmission in heterogeneous networks using satellite communication channels in the context of an undeveloped terrestrial network infrastructure and a remote Internet of things have not yet been carried out. This paper reviews and analyzes protocols and technologies for transferring Internet of Things (IoT) data and presents an architecture for a hybrid IoT-satellite network, which includes a long range (LoRa) low power wide area network (LPWAN) terrestrial network for data collection and an Iridium satellite system for backhaul connectivity. Simulation modelling, together with a specialized experimental stand, allowed us to study the applicability of different methods of information presentation for the case of transmitting IoT data over low-speed satellite communication channels. We proposed a data encoding, compressing, and packaging scheme called GDEPC (Gateway Data Encoding, Packaging and Compressing). It is based on the combination of data format conversion at the connection points of a heterogeneous network, message compressing and packaging. GDEPC enabled the reduction of the number of utilized Short Burst Data (SBD) containers and the overall transmitted data size by almost fifteen times.

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Generalized approach to sentiment analysis of short text messages in natural language processing

2020 · ARTICLE · en

Introduction: Sentiment analysis is a complex problem whose solution essentially depends on the context, field of study and amount of text data. Analysis of publications shows that the authors often do not use the full range of possible data transformations and their combinations. Only a part of the transformations is used, limiting the ways to develop high-quality classification models. Purpose: Developing and exploring a generalized approach to building a model, which consists in sequentially passing through he stages of exploratory data analysis, obtaining a basic solution, vectorization, preprocessing, hyperparameter optimization, and modeling. Results: Comparative experiments conducted using a generalized approach for classical machine learning and deep learning algorithms in order to solve the problem of sentiment analysis of short text messages in natural language processing have demonstrated that the classification quality grows from one stage to another. For classical algorithms, such an increase in quality was insignificant, but for deep learning, it was 8% on average at each stage. Additional studies have shown that the use of automatic machine learning which uses classical classification algorithms is comparable in quality to manual model development; however, it takes much longer. The use of transfer learning has a small but positive effect on the classification quality. Practical relevance: The proposed sequential approach can significantly improve the quality of models under development in natural language processing problems.

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Study of LoRa Performance at 433 MHz and 868 MHz Bands Inside a Multistory Building

2020 · CHAPTER · en

LoRa wireless network has become a widely spread technology among IoT systems recently. LoRa allows to use various ISM bands such as 433 MHz, 868 MHz and 915 MHz. During this study 433 MHz and 868 MHz frequencies have been compared. Parameters such as SNR and RSSI were measured at different floors and visualized. A comparative table of packet delivery ratio at various spreading factors can be found in this paper. A series of range experiments at different spreading factors showed that 433 MHz LoRa module gains a stronger signal. However, 868 MHz LoRa module shows higher percentage of received packets. It has been concluded that for nine-story building with concrete floors it is better to deploy 868 MHz LoRa network at 10th spreading factor.

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Development of an Educational Kit for Learning IoT

2019 · ARTICLE · en

The primary purpose of this paper is to provide an overview of existing education solutions for IoT and develop proposals for their improvement. The study draws analysis of current conditions of the educational IoT sphere, a comparative analysis of educational products used for teaching of undergraduate students. With that the article describes the architecture of our own software and hardware platform for learning IOT. Moreover, this paper reviews methods and technical instruments employed to design software and hardware appliances.

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Energy efficient method of data transmission in a heterogeneous network of the Internet of things for remote areas

2019 · CHAPTER · en

The paper reviewed and analyzed protocols, technologies for transferring and presenting IoT data, developed a model of a heterogeneous IoT network for hard-to-reach areas, proposed a method to improve the efficiency of data transfer in a heterogeneous IoT network. As a result of the work, a model of using the Internet of Things technology (LPWAN) in hard-to-reach areas was developed, information presentation methods were identified that allow solving the problem of collecting information from remote sensors located in the absence of traditional communication channels and a practical check of the results obtained. The paper uses simulation modeling to study the applicability of different methods of presenting information in the case of transmitting IoT data over low-speed satellite communications channels. The method proposed in the paper allowed the use of the Internet of things technology in remote areas using the SBD satellite short message service. The proposed method allowed reducing the volume and number of SBD messages during data transmission via low-speed satellite communication channels, which made it possible to reduce the cost of communication data transmission by 4.82 times.

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Курсы (3)