.png){kind=icon}
Return
Virtual Network Embedding Using Node Multiple Metrics Based on Simplified ELECTRE Method
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2018.2847910.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The concept of network virtualization has attracted significant attention from academia to industry. One of the key challenges in network virtualization is the resource allocation problem, which is also termed the virtual network embedding (VNE) problem. It involved with mapping virtual networks onto a substrate network by adhering to some constraints, such as CPU capacity, on the nodes and bandwidth resources on the links. However, prior heuristic VNE algorithms mostly concentrate on measuring the embedding potential of substrate nodes using the multiplication of different nodes' resource metrics. Due to the fact that different resource metrics have different impacts on node ranking, these traditional methods have some limitations that would cause unbalanced embedding problems. Furthermore, the number of hops for the substrate paths that virtual links are mapped onto will have a large impact on the resource utilization of substrate links in a substrate network. In this paper, based on the topology analysis of six situations, we first propose a novel five-node ranking metric to quantify the importance of substrate nodes. Then, we give a comprehensive measurement method for substrate nodes using the simplified ELECTRE method to avoid an unbalanced embedding solution. We present a novel two-stage VNE algorithm, which chooses the substrate nodes with the maximum embedding potential to perform the node mapping procedure, and uses the shortest path algorithm to accomplish the link mapping procedure. Extensive simulation results demonstrated that our proposed method behaves better than the other state-of-the-art algorithms in terms of the long-term average revenue, the revenue-to-cost (R/C) ratio, and the VN request acceptance ratio.
Keywords:
virtual network embedding
node mapping procedure
link mapping procedure
node ranking metric
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
Cited Papers
ShareSaveConservative treatment feasibility with induction chemotherapy, surgery, and radiotherapy for patients with breast carcinoma larger than 3 cm.png)
CancerOAAI
CancerIF0
OAAIShareSaveShareSaveShareSave
ShareSaveQuark-hadron duality and production of charmonia and doubly charmed baryons in e
+
e
− anninhilationOAAI
OAAIShareSave
View more