75 citations · 171 across the 20 of their papers we have counts for
22 papers
Sentence Specificity Scores for Collaborative Technical Documentation: A Domain-Transfer Study
Rocker D'Antonio, Thomas Benton Townsend, Dimitrios Michael Manias
Collaboration depends on shared context, and technical documentation is one way that context persists across people and AI teammates. Specificity, the amount and exactness of detai…
Lightweight Multi-scale Hierarchical Anomaly Detection and Localization for Geospatial Big Data Applications at the Edge
Thomas Benton Townsend, Joshua Bean, Benjamin K Tkach +2
As an increasing number of critical applications, including environmental, emergency, meteorological, and agricultural, rely on real-time anomaly detection in geospatial data strea…
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…
FALCON-C: Flow-based Analysis and Labeling for Connected Vehicular Network Cybersecurity
Joshua Bean, Dimitrios Michael Manias
Along with the recent rise in popularity of Electric Vehicles (EVs), Electric Vehicle Supply Equipment (EVSE) has emerged as a new target for cyber attacks. Therefore, ensuring the…
Cybersecurity of Electric Vehicle Charging Infrastructure: Recent Advances, Open Challenges, and Future Directions
Joshua Bean, Dimitrios Michael Manias
Electric Vehicles (EVs) have emerged as significant disruptors in the transportation sector over the past decade. Their growing popularity and adoption are accompanied by capital e…
Network Resource Optimization for ML-Based UAV Condition Monitoring with Vibration Analysis
Alexandre Gemayel, Dimitrios Michael Manias, Abdallah Shami
As smart cities begin to materialize, the role of Unmanned Aerial Vehicles (UAVs) and their reliability becomes increasingly important. One aspect of reliability relates to Conditi…
Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis
Alexandre Gemayel, Dimitrios Michael Manias, Abdallah Shami
Unmanned Aerial Vehicles (UAVs) will be critical infrastructural components of future smart cities. In order to operate efficiently, UAV reliability must be ensured by constant mon…
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…
Leveraging Large Language Models for DRL-Based Anti-Jamming Strategies in Zero Touch Networks
Abubakar S. Ali, Dimitrios Michael Manias, Abdallah Shami +1
As the dawn of sixth-generation (6G) networking approaches, it promises unprecedented advancements in communication and automation. Among the leading innovations of 6G is the conce…
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…
Concept Drift Detection in Federated Networked Systems
Dimitrios Michael Manias, Ibrahim Shaer, Li Yang +1
As next-generation networks materialize, increasing levels of intelligence are required. Federated Learning has been identified as a key enabling technology of intelligent and dist…
PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams
Li Yang, Dimitrios Michael Manias, Abdallah Shami
As the number of Internet of Things (IoT) devices and systems have surged, IoT data analytics techniques have been developed to detect malicious cyber-attacks and secure IoT system…
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…
Machine Learning for Performance-Aware Virtual Network Function Placement
Dimitrios Michael Manias, Manar Jammal, Hassan Hawilo +4
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…