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Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G based on SDN/NFV Architecture

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Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G based on SDN/NFV Architecture. / Ibrahim, A.A.Z.; Hashim, F.; Noordin, N.K.; Sali, A.; Navaie, K.; Fadul, S.M.E.

In: IEEE Access, Vol. 9, 24.12.2020, p. 2602-2617.

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Ibrahim, A.A.Z. ; Hashim, F. ; Noordin, N.K. ; Sali, A. ; Navaie, K. ; Fadul, S.M.E. / Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G based on SDN/NFV Architecture. In: IEEE Access. 2020 ; Vol. 9. pp. 2602-2617.

Bibtex

@article{880ad553bc6c432fbe617e64ced8b2af,
title = "Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G based on SDN/NFV Architecture",
abstract = "The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. The distributed multi-controller architecture approach is an emerging strategy that primarily aims to support network functions performed through the application of a control plane, to provide versatile network traffic management. However, the management of resource allocations across multiple data centers is an important issue that still affects 5G core networks. Using such a strategy in 5G core networks requires the controllers to be correctly located, in order to improve network reliability and cost-effectiveness. Thus, to address the controller placement problem (CPP) in a distributed 5G network, we proposed an efficient, heuristic multi-objective optimization approach, using dynamic capacitated controller placement problem (DCCPP). It is based on the K-center problem, to solve the capacitated controller placement problem (CCPP), which acts as a resource location problem, in which the location and number of controllers can be allocated to maximize resources. A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. The design of the heuristic method provides proper load balancing, efficient cost management, and network resource management, as compared to the basic CCPP model. The results indicate that the allocation and the optimum number of controllers under an effective decentralized policy could achieve a higher degree of efficiency through resource assignment in such a densified network. ",
keywords = "5G, 5G mobile communication, Computer architecture, Control systems, controller placement problem, heuristic, Heuristic algorithms, Load management, optimization, resource assignment, Resource management, SDN, Switches, Controllers, Cost effectiveness, Heuristic methods, Information management, Memory architecture, Multiobjective optimization, Network function virtualization, Queueing networks, Resource allocation, Transfer functions, Controller architectures, Controller placements, Decentralized policies, Network functionality, Network resource management, Network traffic management, Resource allocation algorithms, Software defined networking (SDN), 5G mobile communication systems",
author = "A.A.Z. Ibrahim and F. Hashim and N.K. Noordin and A. Sali and K. Navaie and S.M.E. Fadul",
year = "2020",
month = dec,
day = "24",
doi = "10.1109/ACCESS.2020.3047210",
language = "English",
volume = "9",
pages = "2602--2617",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Heuristic Resource Allocation Algorithm for Controller Placement in Multi-Control 5G based on SDN/NFV Architecture

AU - Ibrahim, A.A.Z.

AU - Hashim, F.

AU - Noordin, N.K.

AU - Sali, A.

AU - Navaie, K.

AU - Fadul, S.M.E.

PY - 2020/12/24

Y1 - 2020/12/24

N2 - The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. The distributed multi-controller architecture approach is an emerging strategy that primarily aims to support network functions performed through the application of a control plane, to provide versatile network traffic management. However, the management of resource allocations across multiple data centers is an important issue that still affects 5G core networks. Using such a strategy in 5G core networks requires the controllers to be correctly located, in order to improve network reliability and cost-effectiveness. Thus, to address the controller placement problem (CPP) in a distributed 5G network, we proposed an efficient, heuristic multi-objective optimization approach, using dynamic capacitated controller placement problem (DCCPP). It is based on the K-center problem, to solve the capacitated controller placement problem (CCPP), which acts as a resource location problem, in which the location and number of controllers can be allocated to maximize resources. A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. The design of the heuristic method provides proper load balancing, efficient cost management, and network resource management, as compared to the basic CCPP model. The results indicate that the allocation and the optimum number of controllers under an effective decentralized policy could achieve a higher degree of efficiency through resource assignment in such a densified network.

AB - The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. The distributed multi-controller architecture approach is an emerging strategy that primarily aims to support network functions performed through the application of a control plane, to provide versatile network traffic management. However, the management of resource allocations across multiple data centers is an important issue that still affects 5G core networks. Using such a strategy in 5G core networks requires the controllers to be correctly located, in order to improve network reliability and cost-effectiveness. Thus, to address the controller placement problem (CPP) in a distributed 5G network, we proposed an efficient, heuristic multi-objective optimization approach, using dynamic capacitated controller placement problem (DCCPP). It is based on the K-center problem, to solve the capacitated controller placement problem (CCPP), which acts as a resource location problem, in which the location and number of controllers can be allocated to maximize resources. A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. The design of the heuristic method provides proper load balancing, efficient cost management, and network resource management, as compared to the basic CCPP model. The results indicate that the allocation and the optimum number of controllers under an effective decentralized policy could achieve a higher degree of efficiency through resource assignment in such a densified network.

KW - 5G

KW - 5G mobile communication

KW - Computer architecture

KW - Control systems

KW - controller placement problem

KW - heuristic

KW - Heuristic algorithms

KW - Load management

KW - optimization

KW - resource assignment

KW - Resource management

KW - SDN

KW - Switches

KW - Controllers

KW - Cost effectiveness

KW - Heuristic methods

KW - Information management

KW - Memory architecture

KW - Multiobjective optimization

KW - Network function virtualization

KW - Queueing networks

KW - Resource allocation

KW - Transfer functions

KW - Controller architectures

KW - Controller placements

KW - Decentralized policies

KW - Network functionality

KW - Network resource management

KW - Network traffic management

KW - Resource allocation algorithms

KW - Software defined networking (SDN)

KW - 5G mobile communication systems

U2 - 10.1109/ACCESS.2020.3047210

DO - 10.1109/ACCESS.2020.3047210

M3 - Journal article

VL - 9

SP - 2602

EP - 2617

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -