Location-Aware Energy Efficient Virtual Network Embedding in Software-Defined Optical Data Center Networks

Abstract

To overcome the Internet ossification, network virtualization has been proposed as a promising method because of its advantages (e.g., on demand and efficient resource allocation). Virtual network embedding (VNE) is one of the main challenges for network virtualization. Energy costs of servers in data centers (DCs) are major contribution to power consumption in information and communication technology (ICT). Therefore, VNE should consider both acceptance ratio and power consumption. In this paper, a mixed integer linear programming (MILP) model is proposed with the objective of minimizing the total power consumption in software defined optical data center networks (SD-ODCNs) by reducing the active data centers and power-consuming network components. In addition, the coordinates of nodes and delay of links are considered for more realistic scenario. Comparing with existing node ranking method, proposed global topology resource (GTR) can effectively evaluate the possibility of each DC node to host virtual nodes. Based on GTR method, we propose location aware energy efficient VNE algorithm, namely GTR-VNE. Simulation results show that GTR-VNE can obtain up to 9.3% and 5% improvement of power consumption and acceptance ratio compared with benchmarks. Furthermore, based on GTR and artificial intelligence ant colony optimization (ACO), another energy efficient algorithm ACO-VNE is proposed. ACO-VNE can obtain up to 28.7% improvement on power consumption compared with GTR-VNE. In addition, ACO-VNE has better performance in terms of revenue cost ratio and acceptance ratio.

Parallel, Proactive and Power Efficient Virtual Network Embedding in a Green and Distributed SD-ODCN Architecture

“…Unlike previous research, we address in this paper an intra and inter cloud resources Parallel and Proactive VNE (PGTR-PPVNE), considering various energy types' availabilities in intra and inter cloud levels. We compared all our simulated results with the whole benchmark algorithms mentioned in [11]. The following section describes in detail our proposed solution architecture aiming to maximize REs utilizations, then network and DCs' servers total power efficiency.…”

“…In this later layer, we address a Parallel and Proactive Virtual Network Embedding (PPVNE) sorting the total power efficiency of the whole network components and DCs' servers. Inspired by [11] and our previous complete survey study [12], we propose a mathematical MILP model maximizing total power efficiency in both DCs and inter cloud multi-domain networks components in the SD-ODCN architecture. Contributions in this paper are synthesized as follows: -After instantiating Virtual Network Requests (VNRs) in the SP layer, each user requiring multi-services VNRs at a fixed time stamp may benefit from a parallel and distributed processing in a timely manner.…”

A Survey on the Current Challenges of Energy-Efficient Cloud Resources Management

“…Extensive simulation results demonstrated that the proposed method (E-LB-VNE) can reduce the energy consumption and improve the load balance of substrate network while slightly deteriorating the long-term average revenue, acceptance ratio, and revenue to cost ratio. Again, to minimize total power consumption (router port, EDFAs, OXCs, transponders and servers in DCs) in software-defined optical data center networks (OCDN), study in [51] proposes a global topology resource (GTR) reflecting the selection of each node and link in the substrate network. Based on this GTR method, two energy-efficient VNE algorithms were composed to improve the performance in the scalability of requests and topology.…”

Power-mileage-based Algorithm for the Optimization of Distribution Network Structures via Adding Transmission Lines

“…To determine the power quality of a power grid, many different performance indexes have been proposed [20][21][22][23]. In the adding lines problem, we needed a metric to indicate the voltage profile.…”