Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the tradi...

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Autores principales:	Marios Gatzianas, Agapi Mesodiakaki, George Kalfas, Nikos Pleros, Francesca Moscatelli, Giada Landi, Nicola Ciulli, Leonardo Lossi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	multi-access edge computing virtual network function service function chaining mixed integer linear program network orchestration Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/7d8e0df3970f471481a01b3713c3ba9b
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spelling	oai:doaj.org-article:7d8e0df3970f471481a01b3713c3ba9b2021-11-25T16:31:14ZOffline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks10.3390/app1122105472076-3417https://doaj.org/article/7d8e0df3970f471481a01b3713c3ba9b2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10547https://doaj.org/toc/2076-3417In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.Marios GatzianasAgapi MesodiakakiGeorge KalfasNikos PlerosFrancesca MoscatelliGiada LandiNicola CiulliLeonardo LossiMDPI AGarticlemulti-access edge computingvirtual network functionservice function chainingmixed integer linear programnetwork orchestrationTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10547, p 10547 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multi-access edge computing virtual network function service function chaining mixed integer linear program network orchestration Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	multi-access edge computing virtual network function service function chaining mixed integer linear program network orchestration Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Marios Gatzianas Agapi Mesodiakaki George Kalfas Nikos Pleros Francesca Moscatelli Giada Landi Nicola Ciulli Leonardo Lossi Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
description	In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.
format	article
author	Marios Gatzianas Agapi Mesodiakaki George Kalfas Nikos Pleros Francesca Moscatelli Giada Landi Nicola Ciulli Leonardo Lossi
author_facet	Marios Gatzianas Agapi Mesodiakaki George Kalfas Nikos Pleros Francesca Moscatelli Giada Landi Nicola Ciulli Leonardo Lossi
author_sort	Marios Gatzianas
title	Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
title_short	Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
title_full	Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
title_fullStr	Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
title_full_unstemmed	Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks
title_sort	offline joint network and computational resource allocation for energy-efficient 5g and beyond networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7d8e0df3970f471481a01b3713c3ba9b
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Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

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