Genetic algorithm enabled virtual multicast tree embedding in Software-Defined Networks
| dc.contributor.author | Guler, Evrim | |
| dc.contributor.author | Karakus, Murat | |
| dc.contributor.author | Ayaz, Furkan | |
| dc.date.accessioned | 2026-02-28T12:08:58Z | |
| dc.date.available | 2026-02-28T12:08:58Z | |
| dc.date.issued | 2023 | |
| dc.department | Bayburt Üniversitesi | |
| dc.description.abstract | The recent network virtualization technology enables the multi-tenancy, where various virtual network requests can share the same physical network by decoupling network services from the underlying hardware architecture. The process of virtual node and link mapping onto a shared Substrate Network (SN) by satisfying the requested network resources (i.e., bandwidth, computing capacity, etc.) is referred to as Virtual Network Embedding (VNE), which is known as an NP-Hard problem. The problem of VNE aims to exhibit one-to-one (unicast) communication. However, the motivation of this research is to explore how to efficiently map virtual networks with one-to-many (multicast) communications, which are in the form of Virtual Multicast Trees (VMTs), onto an SN. This problem differs from the traditional VNE problem and has not been well-studied by the research community. To this end, we propose a novel algorithm, Modified Genetic Algorithm for Virtual Multicast Tree Embedding (MGA-VMTE), to embed VMTs onto a shared SN in this research. The proposed MGA-VMTE algorithm focuses on minimizing the network resource consumption (i.e., bandwidth) under end-to-end delay constraint in the SN while satisfying the computing request of virtual nodes. Our extensive simulations demonstrate that the MGA-VMTE algorithm outperforms the dynamic impact factor and traditional greedy-based virtual multicast tree embedding approaches regarding bandwidth consumption, acceptance ratio, and resource depletion ratio metrics on NSFNET, USNET, Random-60 node, and Random-120 node network topologies. © 2022 Elsevier Ltd | |
| dc.identifier.doi | 10.1016/j.jnca.2022.103538 | |
| dc.identifier.issn | 10848045 | |
| dc.identifier.scopus | 2-s2.0-85141892595 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://doi.org/10.1016/j.jnca.2022.103538 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12403/5758 | |
| dc.identifier.volume | 209 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Academic Press | |
| dc.relation.ispartof | Journal of Network and Computer Applications | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20260218 | |
| dc.subject | Embedding | |
| dc.subject | Genetic | |
| dc.subject | Multicast | |
| dc.subject | SDN | |
| dc.subject | Virtualization | |
| dc.title | Genetic algorithm enabled virtual multicast tree embedding in Software-Defined Networks | |
| dc.type | Article |












