Energy-Aware Virtual Network Embedding Approach for Distributed Cloud
Amal S. Alzahrani, Ashraf A. Shahin

TL;DR
This paper introduces an energy-efficient virtual network embedding method for distributed clouds using a particle swarm optimization approach combined with Heavy Clique Matching, improving resource allocation and energy consumption.
Contribution
It presents a novel energy-aware VNE algorithm that partitions virtual networks into subgraphs and optimizes embedding in distributed cloud environments.
Findings
Outperforms existing algorithms in simulations
Reduces energy consumption in virtual network embedding
Enhances resource utilization efficiency
Abstract
Network virtualization has caught the attention of many researchers in recent years. It facilitates the process of creating several virtual networks over a single physical network. Despite this advantage, however, network virtualization suffers from the problem of mapping virtual links and nodes to physical network in most efficient way. This problem is called virtual network embedding ("VNE"). Many researches have been proposed in an attempt to solve this problem, which have many optimization aspects, such as improving embedding strategies in a way that preserves energy, reducing embedding cost and increasing embedding revenue. Moreover, some researchers have extended their algorithms to be more compatible with the distributed clouds instead of a single infrastructure provider ("ISP"). This paper proposes energy aware particle swarm optimization algorithm for distributed clouds. This…
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