Proceedings ArticleDOI
Mapping and Scheduling of Virtual Network Functions using Multi Objective Optimization Algorithm
Mahmoud Gamal,Mehran Abolhasan,Saber Jafarizadeh,Justin Lipman,Wei Ni +4 more
- pp 328-333
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TLDR
A new optimization model has been developed to find the near to optimal mapping and scheduling for the incoming VNF service requests and the resulting algorithm is scalable while considering delay and it outperforms the genetic bandwidth link allocation and genetic non-bandwidth link allocation algorithms.Abstract:
Within the context of Software-Defined Networking (SDN), the problem of resource allocation for a set of incoming Virtual Network Functions (VNF) service requests has been the focus of many studies. In this paper, a new optimization model has been developed to find the near to optimal mapping and scheduling for the incoming VNF service requests. This model while considering delay, aims to achieve three objectives functions, namely, minimizing the transmission delays occurring in every link, minimizing the processing capacity for every Virtual Machine (VM) and minimizing the processing delay at every VM. The resultant problem is formulated as a multi-objective optimization problem and the developed solution is based on a multi-objective evolutionary algorithm utilizing the decomposition algorithm. Simulation results illustrate that the resulting algorithm is scalable while considering delay and it outperforms the genetic bandwidth link allocation (GA-BA) and genetic non-bandwidth link allocation (GA-NBA) algorithms.read more
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Book ChapterDOI
Multi-objective VNF Placement Optimization with NSGA-III
TL;DR: In this paper , the authors investigated the challenge of mapping and scheduling VNFs as a multi-objective optimization problem and proposed an adaptation of the NSGA-III optimization algorithm.
Journal ArticleDOI
Research on Intelligent Mapping Algorithm of Secure Virtual Network under Cloud Computing
Xiaoqiang Niu,Hao Lan,Dan Zeng +2 more
TL;DR: Experimental results show that the percentage of nodes used by the proposed algorithm is much lower than that of other mapping algorithms compared, and the energy consumption is about 8100RMB/h at 60,000 unit time point, indicating that the proposed algorithms has high mapping efficiency.
References
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Journal ArticleDOI
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Qingfu Zhang,Hui Li +1 more
TL;DR: Experimental results have demonstrated that MOEA/D with simple decomposition methods outperforms or performs similarly to MOGLS and NSGA-II on multiobjective 0-1 knapsack problems and continuous multiobjectives optimization problems.
Book
Nonlinear Multiobjective Optimization
TL;DR: This paper is concerned with the development of methods for dealing with the role of symbols in the interpretation of semantics.
Journal ArticleDOI
A survey of network virtualization
TL;DR: The existing technologies and a wide array of past and state-of-the-art projects on network virtualization are surveyed followed by a discussion of major challenges in this area.
Journal ArticleDOI
Resource Allocation in NFV: A Comprehensive Survey
TL;DR: This paper presents a comprehensive state of the art of NFV-RA by introducing a novel classification of the main approaches that pose solutions to solve the NFV resource allocation problem.
Proceedings ArticleDOI
The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances
Qingfu Zhang,Wudong Liu,Hui Li +2 more
TL;DR: The new version of MOEA/D has been tested on all the CEC09 unconstrained MOP test instances and a strategy for allocating the computational resource to different subproblems in MOEA /D is proposed.