LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Distributed Virtual Network Embedding for Software-Defined Networks Using Multiagent Systems

Photo by libby_penner from unsplash

Virtual Network Embedding (VNE), which provides methods to assign multiple Virtual Networks (VN) to a single physical Substrate Network (SN), is an important task in network virtualization. The main problem… Click to show full abstract

Virtual Network Embedding (VNE), which provides methods to assign multiple Virtual Networks (VN) to a single physical Substrate Network (SN), is an important task in network virtualization. The main problem in VNE is the efficiency of assigning customers’ virtual network requests to the substrate network. This problem is known to be a Non-deterministic Polynomial-time hard (NP-hard) and heuristic solutions have been developed to solve this kind of problem. The current trend toward Software-Defined Networking (SDN) has allowed new possibilities in virtual network embedding. In this work, we propose a distributed virtual network embedding for SDNs called DVSDNE using multi-agent systems. This framework could be used to run a centralized VNE algorithm in a distributed manner to scale these algorithms with respect to network size. DVSDNE uses agents to spread the load across the substrate network. Our simulation results show the effectiveness of the proposed algorithm. Results show that DVSDNE improves execution time of embedding algorithms in large scale substrate networks, while embedding results such as acceptance ratio, revenue to cost ratio, average latency to controller, and maximum latency to controller remain comparable.

Keywords: distributed virtual; virtual network; network embedding; software defined; network

Journal Title: IEEE Access
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.