Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …

The network function virtualization (NFV) paradigm is an emerging technology that provides
network flexibility by allowing the allocation of network functions over commodity hardware …

Future communication networksrequire higher bandwidth, greater coverage, and better
throughput. The Space-Air-Ground Integrated Network (SAGIN) has the advantage of wide …

Next-generation 6G networks are envisioned to be a key enabler for low-latency services
(eg, extended reality, remote surgery), which cannot be potentially realized by currently …

Existing Network Function Virtualization (NFV) service placements that reuse already
deployed network functions either reuse an entire Service Function Chain (SFC) or only …

Service Function Chaining (SFC) is regarded as an important concept for next-generation
communication networks because it can flexibly tackle diverse usage scenarios. Due to SFC …

Network service provisioning becomes flexible and programmable with the help of Network
Function Virfitualization (NFV), since NFV abstracts various service functions into software …

Network function virtualization redefines a network service as a softwarized chain of virtual
network functions (VNFs), which decouples the specific network service from dedicated …

In this paper, we study a Deep Reinforcement Learning (DRL) based framework for an
online end-user service provisioning in a Network Function Virtualization (NFV)-enabled …

Edge computing provides computational resources in the vicinity of end-users to reduce
delay compared to traditional remote clouds. However, the capacity of edge resources …