相关论文: TelOps: AI-driven Operations and Maintenance for T…

Age of Information (AoI) has gained importance as a Key Performance Indicator (KPI) for characterizing the freshness of information in information-update systems and time-critical applications. Recent theoretical research on the topic has…

Data is becoming more complex, and so are the approaches designed to process it. Enterprises have access to more data than ever, but many still struggle to glean the full potential of insights from what they have. This research explores the…

Large language model (LLM) agents offer a promising data-driven approach to automating Site Reliability Engineering (SRE), yet their enterprise deployment is constrained by three challenges: restricted access to proprietary data, unsafe…

Telerobotic technologies are becoming increasingly essential in fields such as remote surgery, nuclear decommissioning, and space exploration. Reliable datasets and testbeds are essential for evaluating telerobotic system performance prior…

Deploying machine learning applications on edge devices can bring clear benefits such as improved reliability, latency and privacy but it also introduces its own set of challenges. Most works focus on the limited computational resources of…

Non-terrestrial networks (NTNs) have gained significant attention for their scalability and wide coverage in next-generation communication systems. A large number of NTN nodes, such as satellites, are required to establish a global NTN, but…

Operational Technology (OT) is an integral component of critical national infrastructure, enabling automation and control in industries such as energy, manufacturing, and transportation. However, OT networks, systems, and devices have been…

This paper presents two new challenges for the Telco ecosystem transformation in the era of cloud-native microservice-based architectures. (1) Development-for-Operations (Dev-for-Operations) impacts not only the overall workflow for…

In a telecommunications network, fault alarms generated by network nodes are monitored in a Network Operations Centre (NOC) to ensure network availability and continuous network operations. The monitoring process comprises of tasks such as…

To achieve truly seamless global intelligent connectivity, non-terrestrial networks (NTN) mainly composed of low earth orbit (LEO) satellites and drones are recognized as important components of the future 6G network architecture.…

Multi-agent systems (MAS) powered by LLMs promise adaptive, reasoning-driven enterprise workflows, yet granting agents autonomous control over tools, memory, and communication introduces attack surfaces absent from deterministic pipelines.…

The next-generation wireless networks are evolving into very complex systems because of the very diversified service requirements, heterogeneity in applications, devices, and networks. The mobile network operators (MNOs) need to make the…

The rapid proliferation of generative AI has led to an internet increasingly populated with synthetic content-text, images, audio, and video generated without human intervention. As the distinction between human and AI-generated data blurs,…

The rapid advancements in Artificial Intelligence (AI), particularly in generative AI and foundational models (FMs), have ushered in transformative changes across various industries. Large language models (LLMs), a type of FM, have…

Air Traffic Management data systems today are inefficient and not scalable to enable future unmanned systems. Current data is fragmented, siloed, and not easily accessible. There is data conflict, misuse, and eroding levels of trust in…

Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments. In the AI-enabled UAV-aided wireless networks (UAWN), multiple UAVs are employed as aerial base…

The AIMD algorithm, which underpins the Transmission Control Protocol (TCP) for transporting data packets in communication networks, is perhaps the most successful control algorithm ever deployed. Recently, its use has been extended beyond…

Applying DevOps practices to machine learning system is termed as MLOps and machine learning systems evolve on new data unlike traditional systems on requirements. The objective of MLOps is to establish a connection between different…

Machine learning (ML) has become a popular tool in the industrial sector as it helps to improve operations, increase efficiency, and reduce costs. However, deploying and managing ML models in production environments can be complex. This is…

Sixth-generation (6G) network slicing is the backbone of future communications systems. It inaugurates the era of extreme ultra-reliable and low-latency communication (xURLLC) and pervades the digitalization of the various vertical…