Related papers: Virtual Network Embedding without Explicit Virtual…
The increasing demand for diverse emerging applications has resulted in the interconnection of multi-access edge computing (MEC) systems via metro optical networks. To cater to these diverse applications, network slicing has become a…
The concept of Network Function Virtualization (NFV) has been introduced as a new paradigm in the recent few years. NFV offers a number of benefits including significantly increased maintainability and reduced deployment overhead. Several…
We introduce a general and comprehensive model for the design and optimization of Virtual Networks, and for the related concept of Network Slicing. The model is flexible, so that by adjusting some of its elements, it can accommodate many…
Network functions (e.g., firewalls, load balancers, etc.) have been traditionally provided through proprietary hardware appliances. Often, hardware appliances need to be hardwired back to back to form a service chain providing chained…
Due to the intrinsically inefficient service provisioning in traditional networks, Network Function Virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network…
Virtual network embedding (VNE) is an essential resource allocation task in network virtualization, aiming to map virtual network requests (VNRs) onto physical infrastructure. Reinforcement learning (RL) has recently emerged as a promising…
Infrastructure-as-a-Service (IaaS) providers need to offer richer services to be competitive while optimizing their resource usage to keep costs down. Richer service offerings include new resource request models involving bandwidth…
As an essential resource management problem in network virtualization, virtual network embedding (VNE) aims to allocate the finite resources of physical network to sequentially arriving virtual network requests (VNRs) with different…
Network embedding leverages the node proximity manifested to learn a low-dimensional node vector representation for each node in the network. The learned embeddings could advance various learning tasks such as node classification, network…
We propose a neural embedding algorithm called Network Vector, which learns distributed representations of nodes and the entire networks simultaneously. By embedding networks in a low-dimensional space, the algorithm allows us to compare…
5G is enabling different services over the same physical infrastructure through the concepts and technologies of virtualization, softwarization, slicing and cloud computing. Virtual Mobile Networks (VMNs), using these concepts, provide an…
Over the past few years, the concept of VR has attracted increasing interest thanks to its extensive industrial and commercial applications. Currently, the 3D models of the virtual scenes are generally stored in the VR visor itself, which…
The main issue related to Software-Defined Network emulators is how to replicate real behavior in experiments. Mininet and others SDN emulators have an architecture that limits both the scope of experiments and the fidelity of networking…
Embedding is a useful technique to project a high-dimensional feature into a low-dimensional space, and it has many successful applications including link prediction, node classification and natural language processing. Current approaches…
Recent studies show the increasing popularity of distributed cloud applications, which are composed of multiple microservices. Besides their known benefits, microservice architecture also enables to mix and match cloud applications and…
The concept of network slice, i.e.,a service customized virtual network (VN) is attracting more and more attentions in the telecommunication industry. A slice is a set of network resources which fits the service attributes and requirements…
Network virtualization is a key enabler for 5G systems to support the expected use cases of vertical markets. In this context, we study the joint optimal deployment of Virtual Network Functions (VNFs) and allocation of computational…
Recently, Network Embedding (NE) has become one of the most attractive research topics in machine learning and data mining. NE approaches have achieved promising performance in various of graph mining tasks including link prediction and…
Next Generation Network (NGN) provides multimedia services over broadband based networks, which supports high definition TV (HDTV), and DVD quality video-on-demand content. The video services are thus seen as merging mainly three areas such…
Since real-world objects and their interactions are often multi-modal and multi-typed, heterogeneous networks have been widely used as a more powerful, realistic, and generic superclass of traditional homogeneous networks (graphs).…