TRAFFIC PREDICTION BASED RESOURCE ALLOCATION IN NFV NETWORK ARCHITECTURES INTERCONNECTED BY ELASTIC OPTICAL NETWORKS

Anno
2019
Proponente Vincenzo Eramo - Professore Associato
Sottosettore ERC del proponente del progetto
PE7_8
Componenti gruppo di ricerca
Componente Categoria
Marco Polverini Componenti strutturati del gruppo di ricerca
Antonio Cianfrani Componenti strutturati del gruppo di ricerca
Candeloro Carlo Campanile Dottorando/Assegnista/Specializzando componente non strutturato del gruppo di ricerca
Abstract

The project proposes and investigates reconfiguration policies of cloud and bandwidth resources in Network Function Virtualization environments in which the Network Function Virtualization Infrastructure-Point of Presences are interconnected by an elastic optical network. The proposed policies are applied in dynamic traffic scenarios, they are based on Virtual Network Function Instances migrations and reconfiguration of optical circuits. The policy aims at minimizing the sum of three cost components: the cloud resource cost, the bandwidth cost and the reconfiguration cost. The reconfiguration costs are characterized by the revenue loss of a Network Operator due to the bit loss occurring when the optical circuits are reconfigured. We will formulate the optimization problem and because of its complexity we propose and investigate effective heuristics. The project aims at proving that the proposed heuristics allow, in typical traffic and network scenario, for a consistent cost reduction with respect to the solutions proposed in literature in which only the sum of cloud and bandwidth resource costs are considered and reconfiguration costs are not take into account.
The project is organized in four WPs. In the WP1 an extension of the ETSI NFV architecture will be proposed to support algorithms for the cloud and bandwidth resource reconfiguration. WP2 is devoted to propose reconfiguration algorithms based on the minimization of the sum of cloud, bandwidth and reconfiguration costs and taking into account optical signal quality constraints. traffic prediction algorithms will be studied and integrated to the ones studied in the WP2. The proposed algorithms will be tested in the WP4 by providing numerical results to evaluate the effectiveness of the algorithms.

ERC
PE7_8, PE7_6, PE6_3
Keywords:
RETI DI TELECOMUNICAZIONI, CLOUD COMPUTING, ANALISI DEI COSTI

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