Fog Computing. Группа авторов

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      46 46 IMT vision – framework and overall objectives of the future development of IMT for 2020 and beyond, Recommendation ITU-R M.2083-0, pp. 2083–2090, International Telecommunications Union, 2015.

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      48 48 Yu, F., Chen, H., and Xu, J. (2018). DMPO: dynamic mobility-aware partial offloading in mobile edge computing. Future Generation Computer Systems 89: 722–735.

      49 49 Wang, Z., Zhao, Z., Min, G. et al. (2018). User mobility aware task assignment for mobile edge computing. Future Generation Computer Systems 85: 1–8.

      50 50 Nasrin, W. and Xie, J. (2018). SharedMEC: sharing clouds to support user mobility in mobile edge computing. In: 2018 IEEE International Conference on Communications (ICC), 1–6. IEEE.

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      52 52 Jeong, S., Simeone, O., and Kang, J. (2018). Mobile edge computing via a UAV-mounted cloudlet: optimization of bit allocation and path planning. IEEE Transactions on Vehicular Technology 67 (3): 2049–2063.

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      73 73 Nobre, J.C., de Souza, A.M., Rosário, D. et al. (2019). Vehicular software-defined networking and fog computing: integration and design principles. Ad Hoc Networks 82: 172–181.

      Note

      1 1 www.docker.com.

       Cosmin Avasalcai, Ilir Murturi, and Schahram Dustdar

       Distributed Systems Group, TU Wien, Vienna, Austria

      In the past couple of years, the cloud computing paradigm was at the center of the Internet of Things' (IoT) ever-growing network, where companies can move their control and computing capabilities, and store collected data in a medium with almost unlimited resources [1]. It was and continues to be the best solution to deploy demanding computational applications with the main focus on processing vast amounts of data. Data are generated from geo-distributed IoT devices, such as sensors, smartphones, laptops, and vehicles, just to name a few. However, today this paradigm is facing growing challenges in meeting the demanding constraints of new IoT applications.

      With the rapid adoption of IoT devices, new use cases have emerged to improve our daily lives. Some of these new use cases are the smart city, smart home, smart grid, and smart manufacturing with the power of changing industries (i.e. healthcare, oil and gas, automotive, etc.) by improving the working environment and optimizing workflow. Since most of the use cases consist of multiple applications that require fast response time (i.e. real-time or near real-time) and improved privacy, most of the time the cloud fails to fulfill these requirements (i.e. network congestion and ensuring privacy).

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