Building complex entities like Network Slices and their Subnets requires proper models and
methods to allow their convenient design and deployment. Despite significant progress in …

5G and beyond cellular networks (NextG) will support the continuous execution of resource-
expensive edge-assisted deep learning (DL) tasks. To this end, Radio Access Network …

Based on virtualisation technologies like SDN and NFV, modern networks like 5G create
customised logical networks known as Network Slicing to serve distinct user groups. The …

The next generation of mobile networks (NextG) will require careful resource management
to support edge offloading of resource-intensive deep learning (DL) tasks. Current slicing …

Green Mobile Edge Networks (GMENs) are emerging networks that harvest green energy for
powering mobile edge nodes, thereby reducing carbon dioxide emissions and energy costs …

With the advancement of intelligent transportation systems, a series of diversified V2X
applications come into being, which have different key performance indicators (KPIs) and …

In cell-free wireless networks, multiple connectivity options and technologies are available to
serve each user. Traditionally, such options are ranked and selected solely based on the …

The existing work on the distributed training of machine learning (ML) models has
consistently overlooked the distribution of the achieved learning quality, focusing instead on …

Deploying services efficiently while satisfying their quality requirements is a major challenge
in network slicing. Effective solutions place instances of the services' virtual network …