Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles
The expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network (SDN...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-10-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/13/11/270 |
| _version_ | 1797510203936079872 |
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| author | Rhodney Simões Kelvin Dias Ricardo Martins |
| author_facet | Rhodney Simões Kelvin Dias Ricardo Martins |
| author_sort | Rhodney Simões |
| collection | DOAJ |
| description | The expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network (SDN) based Internet of Vehicles (IoV). At the heart of this issue is the need for an architecture and optimization mechanisms that benefit from cutting edge technologies while granting latency bounds in order to control and manage the dynamic nature of IoV. To this end, this article proposes an autonomic software-defined vehicular architecture grounded on the synergy of Multi-access Edge Computing (MEC) and Network Functions Virtualization (NFV) along with a heuristic approach and an exact model based on linear programming to efficiently optimize the dynamic resource allocation of SDN controllers, ensuring load balancing between controllers and employing reserve resources for tolerance in case of demand variation. The analyses carried out in this article consider: (a) to avoid waste of limited MEC resources, (b) to devise load balancing among controllers, (c) management complexity, and (d) to support scalability in dense IoV scenarios. The results show that the heuristic efficiently manages the environment even in highly dynamic and dense scenarios. |
| first_indexed | 2024-03-10T05:28:16Z |
| format | Article |
| id | doaj.art-206af43d342d47e5a75d93b6da29e601 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-10T05:28:16Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-206af43d342d47e5a75d93b6da29e6012023-11-22T23:26:20ZengMDPI AGFuture Internet1999-59032021-10-01131127010.3390/fi13110270Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of VehiclesRhodney Simões0Kelvin Dias1Ricardo Martins2Centro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, PE, BrazilCentro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, PE, BrazilCentro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, PE, BrazilThe expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network (SDN) based Internet of Vehicles (IoV). At the heart of this issue is the need for an architecture and optimization mechanisms that benefit from cutting edge technologies while granting latency bounds in order to control and manage the dynamic nature of IoV. To this end, this article proposes an autonomic software-defined vehicular architecture grounded on the synergy of Multi-access Edge Computing (MEC) and Network Functions Virtualization (NFV) along with a heuristic approach and an exact model based on linear programming to efficiently optimize the dynamic resource allocation of SDN controllers, ensuring load balancing between controllers and employing reserve resources for tolerance in case of demand variation. The analyses carried out in this article consider: (a) to avoid waste of limited MEC resources, (b) to devise load balancing among controllers, (c) management complexity, and (d) to support scalability in dense IoV scenarios. The results show that the heuristic efficiently manages the environment even in highly dynamic and dense scenarios.https://www.mdpi.com/1999-5903/13/11/270dynamic allocation of controllersSDNNFV-based MEC architectureIoVhigh-density scenarios |
| spellingShingle | Rhodney Simões Kelvin Dias Ricardo Martins Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles Future Internet dynamic allocation of controllers SDN NFV-based MEC architecture IoV high-density scenarios |
| title | Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles |
| title_full | Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles |
| title_fullStr | Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles |
| title_full_unstemmed | Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles |
| title_short | Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles |
| title_sort | dynamic allocation of sdn controllers in nfv based mec for the internet of vehicles |
| topic | dynamic allocation of controllers SDN NFV-based MEC architecture IoV high-density scenarios |
| url | https://www.mdpi.com/1999-5903/13/11/270 |
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