Related papers: Intelligent Routing as a Service (iRaaS)
Sixth generation (6G) networks demand tight integration of artificial intelligence (AI) into radio access networks (RANs) to meet stringent quality of service (QoS) and resource efficiency requirements. Existing solutions struggle to bridge…
To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in…
With the rapid development of software defined networking and network function virtualization, researchers have proposed a new cloud networking model called Network-as-a-Service (NaaS) which enables both in-network packet processing and…
The Internet of Things (IoT) establishes connectivity between billions of heterogeneous devices that provide a variety of essential everyday services. The IoT faces several challenges, including energy efficiency and scalability, that…
This paper aims to develop the intelligent traffic steering (TS) framework, which has recently been considered as one of the key developments of 3GPP for advanced 5G. Since achieving key performance indicators (KPIs) for heterogeneous…
Modern communication networks are increasingly equipped with in-network computational capabilities and services. Routing in such networks is significantly more complicated than the traditional routing. A legitimate route for a flow not only…
It is envisioned that 6G networks will be supported by key architectural principles, including intelligence, decentralization, interoperability, and digitalization. With the advances in artificial intelligence (AI) and machine learning…
The increasing adoption of UAVs with advanced sensors and GPU-accelerated edge computing has enabled real-time AI-driven applications in fields such as precision agriculture, wildfire monitoring, and environmental conservation. However,…
On-demand service provisioning is a critical yet challenging issue in 6G wireless communication networks, since emerging services have significantly diverse requirements and the network resources become increasingly heterogeneous and…
The proliferation of intelligent transportation systems (ITS) has led to increasing demand for diverse network applications. However, conventional terrestrial access networks (TANs) are inadequate in accommodating various applications for…
Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, most of the solutions available today face scalability issues…
The rapid emergence of AI-powered applications is reshaping the role of the Internet. Users increasingly rely on the network to obtain intelligence services derived from large foundation models, rather than merely to reach remote endpoints…
6G networks are expected to revolutionize connectivity, offering significant improvements in speed, capacity, and smart automation. However, existing network designs will struggle to handle the demands of 6G, which include much faster…
Reconfigurable Intelligent Surfaces (RIS) enable dynamic electromagnetic control for 6G networks, but existing control schemes lack responsiveness to fast-varying network conditions, limiting their applicability for ultra-reliable low…
Emerging on-demand connectivity scenarios increasingly require networking solutions with stringent service-level guarantees. We propose Swarm Network-as-a-Service (SNaaS), a service-oriented framework that leverages fleets of drones to…
The growing demand for high-speed, reliable wireless connectivity in 6G networks necessitates innovative approaches to overcome the limitations of traditional Radio Access Network (RAN). Reconfigurable Intelligent Surface (RIS) and…
The emergence of the fifth generation (5G) technology has transformed mobile networks into multi-service environments, necessitating efficient network slicing to meet diverse Service Level Agreements (SLAs). SLA decomposition across…
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, text, and vision. At the same time, the "as-a-Service"-based…
Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most current methods are "coupled" in such a way that they generate explanations simultaneously with…
This paper addresses how to handle slice resources for 6G networks at different time scales in an architecture based on an open radio access network (ORAN). The proposed solution includes artificial intelligence (AI) at the edge of the…