Wyniki wyszukiwania dla: CLOUD COMPUTING, IAAS CLOUD, RESOURCES, BIG DATA, INTERNET OF THINGS, IOT - MOST Wiedzy

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Wyniki wyszukiwania dla: CLOUD COMPUTING, IAAS CLOUD, RESOURCES, BIG DATA, INTERNET OF THINGS, IOT
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Wyniki wyszukiwania dla: CLOUD COMPUTING, IAAS CLOUD, RESOURCES, BIG DATA, INTERNET OF THINGS, IOT

  • Big Data and the Internet of Things in Edge Computing for Smart City

    Publikacja

    - Rok 2019

    Requests expressing collective human expectations and outcomes from city service tasks can be partially satisfied by processing Big Data provided to a city cloud via the Internet of Things. To improve the efficiency of the city clouds an edge computing has been introduced regarding Big Data mining. This intelligent and efficient distributed system can be developed for citizens that are supposed to be informed and educated by the...

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  • On the impact of Big Data and Cloud Computing on a scalable multimedia archiving system

    Multimedia Archiver (MA) is a system build upon the promise and fascination of the possibilities emerging from cloud computing and big data. We aim to present and describe how the Multimedia Archiving system works for us to record, put in context and allow a swift access to large amounts of data. We introduce the architecture, identified goals and needs taken into account while designing a system processing data with Big Data...

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  • Mobile devices and computing cloud resources allocation for interactive applications

    Using mobile devices such as smartphones or iPads for various interactive applications is currently very common. In the case of complex applications, e.g. chess games, the capabilities of these devices are insufficient to run the application in real time. One of the solutions is to use cloud computing. However, there is an optimization problem of mobile device and cloud resources allocation. An iterative heuristic algorithm for...

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  • Krzysztof Goczyła prof. dr hab. inż.

    Krzysztof Goczyła, profesor zwyczajny Politechniki Gdańskiej, informatyk, specjalista z inżynierii oprogramowania, inżynierii wiedzy i baz danych. Ukończył studia wyższe na  Wydziale Elektroniki Politechniki Gdańskiej w 1976 r. jako magister inżynier elektronik w specjalności automatyka. Na Politechnice Gdańskiej pracuje od 1976. Na Wydziale Elektroniki PG w 1982 r. uzyskał doktorat z informatyki, a w 1999 r. habilitację. W 2012...

  • Krzysztof Gierłowski dr inż.

    Krzysztof Gierłowski uzyskał tytuł doktora inżyniera telekomunikacji na Wydziale Elektroniki, Telekomunikacji i Informatyki w 2018 roku. Jest autorem lub współautorem ponad 80 publikacji naukowych oraz recenzentem wielu czasopism i konferencji. Brał udział w szeregu projektów badawczych dotyczących tematyki IT, wliczając w to: finansowany ze źródeł UE projekt Inżynieria Internetu Przyszłości, projekt infrastrukturalny PL-LAB2020,...

  • Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City

    Publikacja

    - Rok 2021

    Data from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...

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  • Review of the Complexity of Managing Big Data of the Internet of Things

    Publikacja

    - COMPLEXITY - Rok 2019

    Tere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...

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  • Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud

    The paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.

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  • Processing of Satellite Data in the Cloud

    Publikacja

    The dynamic development of digital technologies, especially those dedicated to devices generating large data streams, such as all kinds of measurement equipment (temperature and humidity sensors, cameras, radio-telescopes and satellites – Internet of Things) enables more in-depth analysis of the surrounding reality, including better understanding of various natural phenomenon, starting from atomic level reactions, through macroscopic...

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  • Complementary oriented allocation algorithm for cloud computing

    Publikacja

    Nowadays cloud computing is one of the most popular processing models. More and more different kinds of workloads have been migrated to clouds. This trend obliges the community to design algorithms which could optimize the usage of cloud resources and be more effiient and effective. The paper proposes a new model of workload allocation which bases on the complementarity relation and analyzes it. An example of a case of use is shown...

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