… nodes, which are connected by virtual links. The purpose of virtual network embedding is to
map virtual networks to shared physical networks while providing sufficient computation and …

… In this paper, to solve the automatic virtual network embedding problem, we have adopted
the state-of-the-art deep reinforcement learning techniques. To speed up the training …

… Virtual network embedding (VNE) is the core orientation of VN… the dynamic characteristics
of virtual network request (VNR) … -decision virtual network embedding scheme relying on rein…

… The problem is known in the networking community under the name Virtual Network
Embedding Problem (VNEP). It has been studied intensively for over a decade in various contexts …

… solution can be presented as a sequence: {(0, 1), (1, 0), (2, 6), (3, 2)}, which represents a
probe of an embedding scheme of the agent. The state sets, actions sets and the sequence of …

… cross-network deep network embedding (CDNE) model is proposed to incorporate domain
adaptation into deep network embedding in order to learn label-discriminative and network-…

… virtual network function (NF) placement are studied for accommodating multicast services
over an NFV-enabled physical substrate network. … the flexible scheme; (d) Embedding result of …

… virtual network environment. This paper proposes a bandwidth aware multi domain virtual
network embedding (BA… of the particle and the embedding cost of the embedding scheme. (3) …

… Based on virtual network architecture and deep reinforcement … as a multi-domain virtual
network embedding (VNE) problem, … scheme, virtual node a is mapped to satellite node B, virtual …

… Furthermore, we also design a scheme to solve the problem of large action space while …
the impact of perVNF embeddings and global substrate network embedding on Kolin’s …