75 citations · 171 across the 20 of their papers we have counts for
12 papers · 1 filter
Advanced LLM-Enhanced Intent-Based 5G Network Management using Dynamic Semantic Routes
Thomas Benton Townsend, Dimitrios Michael Manias
As the use of Artificial Intelligence (AI) and Large Language Models (LLMs) is becoming common in everyday applications, their ability to interpret natural language has increased s…
Semantic Routing for Enhanced Performance of LLM-Assisted Intent-Based 5G Core Network Management and Orchestration
Dimitrios Michael Manias, Ali Chouman, Abdallah Shami
Large language models (LLMs) are rapidly emerging in Artificial Intelligence (AI) applications, especially in the fields of natural language processing and generative AI. Not limit…
A Modular, End-to-End Next-Generation Network Testbed: Towards a Fully Automated Network Management Platform
Ali Chouman, Dimitrios Michael Manias, Abdallah Shami
Experimentation in practical, end-to-end (E2E) next-generation networks deployments is becoming increasingly prevalent and significant in the realm of modern networking and wireles…
Probabilistic Fault-Tolerant Robust Traffic Grooming in OTN-over-DWDM Networks
Dimitrios Michael Manias, Joe Naoum-Sawaya, Abbas Javadtalab +1
The development of next-generation networks is revolutionizing network operators' management and orchestration practices worldwide. The critical services supported by these network…
Towards Intent-Based Network Management: Large Language Models for Intent Extraction in 5G Core Networks
Dimitrios Michael Manias, Ali Chouman, Abdallah Shami
The integration of Machine Learning and Artificial Intelligence (ML/AI) into fifth-generation (5G) networks has made evident the limitations of network intelligence with ever-incre…
An NWDAF Approach to 5G Core Network Signaling Traffic: Analysis and Characterization
Dimitrios Michael Manias, Ali Chouman, Abdallah Shami
Data-driven approaches and paradigms have become promising solutions to efficient network performances through optimization. These approaches focus on state-of-the-art machine lear…
A Model Drift Detection and Adaptation Framework for 5G Core Networks
Dimitrios Michael Manias, Ali Chouman, Abdallah Shami
The advent of Fifth Generation (5G) and beyond 5G networks (5G+) has revolutionized the way network operators consider the management and orchestration of their networks. With an i…
Towards Supporting Intelligence in 5G/6G Core Networks: NWDAF Implementation and Initial Analysis
Ali Chouman, Dimitrios Michael Manias, Abdallah Shami
Wireless networks, in the fifth-generation and beyond, must support diverse network applications which will support the numerous and demanding connections of today's and tomorrow's…
Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems
Dimitrios Michael Manias, Abdallah Shami
With the incoming introduction of 5G networks and the advancement in technologies, such as Network Function Virtualization and Software Defined Networking, new and emerging network…
The Need for Advanced Intelligence in NFV Management and Orchestration
Dimitrios Michael Manias, Abdallah Shami
With the constant demand for connectivity at an all-time high, Network Service Providers (NSPs) are required to optimize their networks to cope with rising capital and operational…
A Machine Learning-Based Migration Strategy for Virtual Network Function Instances
Dimitrios Michael Manias, Hassan Hawilo, Abdallah Shami
With the growing demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while simultaneously improving n…
Depth-Optimized Delay-Aware Tree (DO-DAT) for Virtual Network Function Placement
Dimitrios Michael Manias, Hassan Hawilo, Manar Jammal +1
With the constant increase in demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while ensuring cont…