DeViNE: A Decentralized Virtual Network Embedding Algorithm
Farzad Habibi, Juncheng Fang

TL;DR
DeViNE introduces a decentralized virtual network embedding algorithm that enhances scalability and robustness, outperforming centralized methods in acceptance rate and revenue-to-cost ratio.
Contribution
This paper presents a novel decentralized VNE algorithm that addresses scalability and robustness issues of prior centralized approaches using leader election and local embedding.
Findings
12% higher acceptance rate compared to existing methods.
Approximately 21% improvement in revenue-to-cost ratio.
Demonstrates enhanced scalability and robustness through decentralization.
Abstract
Virtual Network Embedding (VNE) is a technique for mapping virtual networks onto a physical network infrastructure, enabling multiple virtual networks to coexist on a shared physical network. Previous works focused on implementing centralized VNE algorithms, which suffer from lack of scalability and robustness. This project aims to implement a decentralized virtual network embedding algorithm that addresses the challenges of network virtualization, such as scalability, single point of failure, and DoS attacks. The proposed approach involves selecting L leaders from the physical nodes and embedding a virtual network request (VNR) in the local network of each leader using a simple algorithm like BFS. The algorithm then uses a leader-election mechanism for determining the node with the lowest cost and highest revenue and propagates the embedding to other leaders. By utilizing…
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Taxonomy
TopicsSoftware-Defined Networks and 5G · Advanced Graph Neural Networks · Network Packet Processing and Optimization
