A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks
The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/21/6017 |
| _version_ | 1797550038927278080 |
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| author | Sanjay Kumar Biswash Dushantha Nalin K. Jayakody |
| author_facet | Sanjay Kumar Biswash Dushantha Nalin K. Jayakody |
| author_sort | Sanjay Kumar Biswash |
| collection | DOAJ |
| description | The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks. |
| first_indexed | 2024-03-10T15:23:49Z |
| format | Article |
| id | doaj.art-8f9e0c32bccc46d8a5425f2c21ab5cf7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:23:49Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8f9e0c32bccc46d8a5425f2c21ab5cf72023-11-20T18:15:20ZengMDPI AGSensors1424-82202020-10-012021601710.3390/s20216017A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G NetworksSanjay Kumar Biswash0Dushantha Nalin K. Jayakody1School of Computer Science and Robotics, National Research Tomsk Polytechnic University, 634050 Tomsk, RussiaSchool of Computer Science and Robotics, National Research Tomsk Polytechnic University, 634050 Tomsk, RussiaThe fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks.https://www.mdpi.com/1424-8220/20/21/6017fog networks5G networksdevice-driven communicationsdata-centric networking |
| spellingShingle | Sanjay Kumar Biswash Dushantha Nalin K. Jayakody A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks Sensors fog networks 5G networks device-driven communications data-centric networking |
| title | A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks |
| title_full | A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks |
| title_fullStr | A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks |
| title_full_unstemmed | A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks |
| title_short | A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks |
| title_sort | fog computing based device driven mobility management scheme for 5g networks |
| topic | fog networks 5G networks device-driven communications data-centric networking |
| url | https://www.mdpi.com/1424-8220/20/21/6017 |
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