%0 Conference Proceedings
%T Experimental Evaluation of Dynamic Resource Orchestration in Multi-layer (Packet over Flexi-Grid Optical) Networks
%+ Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)
%+ Consiglio Nazionale delle Ricerche Area della Ricerca di Pisa (CNIT)
%+ Centre Tecnològic de Telecomunicacions de Catalunya = Telecommunications Technological Centre of Catalonia (CTTC)
%A Fichera, Silvia
%A Martini, Barbara
%A Martínez, Ricardo
%A Casellas, Ramon
%A Vilalta, Ricard
%A Muñoz, Raul
%A Castoldi, Piero
%Z Part 1: Regular Papers
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 23th International IFIP Conference on Optical Network Design and Modeling (ONDM)
%C Athens, Greece
%Y Anna Tzanakaki
%Y Manos Varvarigos
%Y Raul Muñoz
%Y Reza Nejabati
%Y Noboru Yoshikane
%Y Markos Anastasopoulos
%Y Johann Marquez-Barja
%I Springer International Publishing
%3 Optical Network Design and Modeling
%V LNCS-11616
%P 261-273
%8 2019-05-13
%D 2019
%R 10.1007/978-3-030-38085-4_23
%K Resource orchestration
%K SDN
%K NFV
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X In future 5G infrastructures, network services will be deployed through sets of Virtual Network Functions (VNFs) leveraging the advantages of both Software Defined Networking (SDN) and Network Function Virtualization (NFV). A network service is composed of an ordered sequence of VNFs, i.e., VNF Forwarding Graph (VNFFG), deployed across distributed data centers (DCs). Herein, we present a Cloud/Network Orchestrator which dynamically processes and accommodates VNFFG requests over a pool of DCs interconnected by a multi-layer (packet/flexi-grid optical) transport network infrastructure. We propose two different cloud and network resource allocation algorithms aiming at: (i) minimizing the distance between the selected DCs, and (ii) minimizing the load (i.e., consumed cloud resources) of the chosen DCs. Both algorithms run on a Cloud/Network Orchestrator and are experimentally validated and benchmarked on the CTTC ADRENALINE testbed.
%G English
%Z TC 6
%Z WG 6.10
%2 https://inria.hal.science/hal-03200646/document
%2 https://inria.hal.science/hal-03200646/file/484327_1_En_23_Chapter.pdf
%L hal-03200646
%U https://inria.hal.science/hal-03200646
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-LNCS-11616
%~ IFIP-ONDM
%~ IFIP-WG6-10