5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services

A. Akman; V. Monteiro; P. Marques; J. Rodriguez; P. Vieira; H. Marques; A. Abdalla

doi:10.1109/CAMAD50429.2020.9209310

5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services

A. Akman, V. Monteiro, P. Marques, J. Rodriguez, P. Vieira, H. Marques, A. Abdalla

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

5G has a number of challenges to solve. Higher data usage and processing power necessities have emerged from the increasing number of mobile users as well as mobile applications becoming more and more demanding. There is a significant need to reduce the latency of the mobile network while cutting down on energy consumption. Backhaul traffic needs to be optimized to avoid setting up costly backhaul connections. Many IoT scenarios have conflicting requirements; the need for cheap and low complexity devices vs the need for processing power. Operators need to come up with value added services to avoid being dumb-pipe operators. The answer to these challenges and more require cloud-computing capabilities within the Radio Access Network (RAN) as well as a platform for mobile operators and third-party application providers to utilize these computing capabilities. This is where Mobile Edge Computing (MEC), one of the key emerging technologies for 5G, comes into play. The 5GMEDE project proposes to not only develop and demonstrate a complete MEC solution, including the MEC framework, Base Station services and applications to run on top, but also offers innovative features like constraint based mobile edge selection, using data analytics to enrich and refine real-time radio network information and utilizing Software Defined Wireless Networks (SDWN) concepts to improve mobility and resource allocation services to enable operators.

Original language	English
Title of host publication	2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	978-1-7281-6339-0, 978-1-7281-6340-6
DOIs	https://doi.org/10.1109/CAMAD50429.2020.9209310
Publication status	Published - Sept 2020
Externally published	Yes
Event	25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Pisa, Italy Duration: 14 Sept 2020 → 16 Sept 2020

Conference

Conference	25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020
Country/Territory	Italy
City	Pisa
Period	14/09/20 → 16/09/20

Keywords

5G
Energy Efficiency
MEC
RAN

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CAMAD50429.2020.9209310

Cite this

Akman, A., Monteiro, V., Marques, P., Rodriguez, J., Vieira, P., Marques, H., & Abdalla, A. (2020). 5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services. In 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings Article 9209310 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMAD50429.2020.9209310

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title = "5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services",

abstract = "5G has a number of challenges to solve. Higher data usage and processing power necessities have emerged from the increasing number of mobile users as well as mobile applications becoming more and more demanding. There is a significant need to reduce the latency of the mobile network while cutting down on energy consumption. Backhaul traffic needs to be optimized to avoid setting up costly backhaul connections. Many IoT scenarios have conflicting requirements; the need for cheap and low complexity devices vs the need for processing power. Operators need to come up with value added services to avoid being dumb-pipe operators. The answer to these challenges and more require cloud-computing capabilities within the Radio Access Network (RAN) as well as a platform for mobile operators and third-party application providers to utilize these computing capabilities. This is where Mobile Edge Computing (MEC), one of the key emerging technologies for 5G, comes into play. The 5GMEDE project proposes to not only develop and demonstrate a complete MEC solution, including the MEC framework, Base Station services and applications to run on top, but also offers innovative features like constraint based mobile edge selection, using data analytics to enrich and refine real-time radio network information and utilizing Software Defined Wireless Networks (SDWN) concepts to improve mobility and resource allocation services to enable operators.",

keywords = "5G, Energy Efficiency, MEC, RAN",

author = "A. Akman and V. Monteiro and P. Marques and J. Rodriguez and P. Vieira and H. Marques and A. Abdalla",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 ; Conference date: 14-09-2020 Through 16-09-2020",

year = "2020",

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doi = "10.1109/CAMAD50429.2020.9209310",

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booktitle = "2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings",

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Akman, A, Monteiro, V, Marques, P, Rodriguez, J, Vieira, P, Marques, H & Abdalla, A 2020, 5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services. in 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings., 9209310, Institute of Electrical and Electronics Engineers Inc., 25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020, Pisa, Italy, 14/09/20. https://doi.org/10.1109/CAMAD50429.2020.9209310

5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services. / Akman, A.; Monteiro, V.; Marques, P. et al.
2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9209310.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - 5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services

AU - Akman, A.

AU - Monteiro, V.

AU - Marques, P.

AU - Rodriguez, J.

AU - Vieira, P.

AU - Marques, H.

AU - Abdalla, A.

PY - 2020/9

Y1 - 2020/9

N2 - 5G has a number of challenges to solve. Higher data usage and processing power necessities have emerged from the increasing number of mobile users as well as mobile applications becoming more and more demanding. There is a significant need to reduce the latency of the mobile network while cutting down on energy consumption. Backhaul traffic needs to be optimized to avoid setting up costly backhaul connections. Many IoT scenarios have conflicting requirements; the need for cheap and low complexity devices vs the need for processing power. Operators need to come up with value added services to avoid being dumb-pipe operators. The answer to these challenges and more require cloud-computing capabilities within the Radio Access Network (RAN) as well as a platform for mobile operators and third-party application providers to utilize these computing capabilities. This is where Mobile Edge Computing (MEC), one of the key emerging technologies for 5G, comes into play. The 5GMEDE project proposes to not only develop and demonstrate a complete MEC solution, including the MEC framework, Base Station services and applications to run on top, but also offers innovative features like constraint based mobile edge selection, using data analytics to enrich and refine real-time radio network information and utilizing Software Defined Wireless Networks (SDWN) concepts to improve mobility and resource allocation services to enable operators.

AB - 5G has a number of challenges to solve. Higher data usage and processing power necessities have emerged from the increasing number of mobile users as well as mobile applications becoming more and more demanding. There is a significant need to reduce the latency of the mobile network while cutting down on energy consumption. Backhaul traffic needs to be optimized to avoid setting up costly backhaul connections. Many IoT scenarios have conflicting requirements; the need for cheap and low complexity devices vs the need for processing power. Operators need to come up with value added services to avoid being dumb-pipe operators. The answer to these challenges and more require cloud-computing capabilities within the Radio Access Network (RAN) as well as a platform for mobile operators and third-party application providers to utilize these computing capabilities. This is where Mobile Edge Computing (MEC), one of the key emerging technologies for 5G, comes into play. The 5GMEDE project proposes to not only develop and demonstrate a complete MEC solution, including the MEC framework, Base Station services and applications to run on top, but also offers innovative features like constraint based mobile edge selection, using data analytics to enrich and refine real-time radio network information and utilizing Software Defined Wireless Networks (SDWN) concepts to improve mobility and resource allocation services to enable operators.

KW - 5G

KW - Energy Efficiency

KW - MEC

KW - RAN

U2 - 10.1109/CAMAD50429.2020.9209310

DO - 10.1109/CAMAD50429.2020.9209310

M3 - Conference contribution

AN - SCOPUS:85093934181

BT - 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020

Y2 - 14 September 2020 through 16 September 2020

ER -

Akman A, Monteiro V, Marques P, Rodriguez J, Vieira P, Marques H et al. 5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services. In 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9209310 doi: 10.1109/CAMAD50429.2020.9209310

5GMEDE - 5G Mobile Edge Computing with Enriched Radio Network Information Services

Abstract

Conference

Keywords

UN SDGs

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Cite this