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Optimal virtual network embedding: Energy aware formulation
Publikationstyp
Journal Article
Date Issued
2015
Sprache
English
Institut
TORE-URI
Journal
Volume
91
Start Page
184
End Page
195
Citation
Computer Networks (91): 184-195 (2015)
Publisher DOI
Scopus ID
Network Virtualization is a key component of the Future Internet, providing the dynamic support of different networks with different paradigms and mechanisms in the same physical infrastructure. A major challenge in the dynamic provision of virtual networks is the embedding approach taking energy efficiency into account, while not affecting the overall Virtual Network (VN) acceptance ratio. Previous research focused on either designing heuristic-based algorithms to address the efficient embedding problem or to address the energy impact. This paper proposes an integer linear programming formulation, Energy Aware-Virtual Network Embedding-Node-Link Formulation (EA-VNE-NLF), that solves the online virtual network embedding as an optimization problem, striving for the minimum energy consumption and optimal resource allocation per VN mapping. Two different objective functions are proposed: (i) addressing primarily the resource consumption problem - Bandwidth Consumption Minimization (BCM); (ii) addressing primarily the energy consumption problem - Energy Consumption Minimization (ECM). The performance of each objective function is evaluated by means of simulation and compared with an existing objective function, Weighted Shortest Distance Path (WSDP), that is considered state of the art of the resource allocation problem. The simulation results show that the objective function BCM reduces the energy consumption of the physical network by 14.4%, and improves the embedding factor by 4.3%, consuming almost the same amount of resources as requested, and slightly worsening the VN acceptance ratio by 2.3%. ECM reduces the energy consumption of the physical network by 31.4% and improves the embedding factor by 4.1%, without affecting the VN acceptance ratio when compared to WSDP.
Subjects
Energy
ILP Model
Mapping
Network virtualization
Optimization