An NDN-Enabled Fog Radio Access Network Architecture With Distributed In-Network Caching

To meet the increasing demands of next-generation cellular networks (e.g., 6G), advanced networking technologies must be incorporated. On one hand, the Fog Radio Access Network (F-RAN), has been proposed as an enhancement to the Cloud Radio Access Network (C-RAN). On the other hand, efficient network architectures, such as Named Data Networking (NDN), have been recognized as prominent Future Internet candidates. Nevertheless, the interplay between F-RAN and NDN warrants further investigation. In this paper, we propose an NDN-enabled F-RAN architecture featuring a strategy for distributed in-network caching. Through a simulation study, we demonstrate the superiority of the proposed in-network caching strategy in comparison with baseline caching strategies in terms of network resource utilization, cache hits, and fronthaul channel usage.Comment: Accepted for publication by IEEE ICC 202

Rethinking Internet Communication Through LLMs: How Close Are We?

In this paper, we rethink the way that communication among users over the Internet, one of the fundamental outcomes of the Internet evolution, takes place. Instead of users communicating directly over the Internet, we explore an architecture that enables users to communicate with (query) Large Language Models (LLMs) that capture the cognition of users on the other end of the communication channel. We present an architecture to achieve such LLM-based communication and we perform a reality check to assess how close we are today to realizing such a communication architecture from a technical point of view. Finally, we discuss several research challenges and identify interesting directions for future research

ARWalker: A Virtual Walking Companion Application

Extended Reality (XR) technologies, including Augmented Reality (AR), have attracted significant attention over the past few years and have been utilized in several fields, including education, healthcare, and manufacturing. In this paper, we aim to explore the use of AR in the field of biomechanics and human movement through the development of ARWalker, which is an AR application that features virtual walking companions (avatars). Research participants walk in close synchrony with the virtual companions, whose gait exhibits properties found in the gait of young and healthy adults. As a result, research participants can train their gait to the gait of the avatar, thus regaining the healthy properties of their gait and reducing the risk of falls. ARWalker can especially help older adults and individuals with diseases, who exhibit pathological gait thus being more prone to falls. We implement a prototype of ARWalker and evaluate its systems performance while running on a Microsoft Hololens 2 headset

A Nonlinear Analysis Software Toolkit for Biomechanical Data

In this paper, we present a nonlinear analysis software toolkit, which can help in biomechanical gait data analysis by implementing various nonlinear statistical analysis algorithms. The toolkit is proposed to tackle the need for an easy-to-use and friendly analyzer for gait data where algorithms seem complex to implement in software and execute. With the availability of our toolkit, people without programming knowledge can run the analysis to receive human gait data analysis results. Our toolkit includes the implementation of several nonlinear analysis algorithms, while it is also possible for users with programming experience to expand its scope by implementing and adding more algorithms to the toolkit. Currently, the toolkit supports MatLab bindings while being developed in Python. The toolkit can seamlessly run as a background process to analyze hundreds of different gait data and produce analysis outcomes and figures that illustrate these results

ICedge: When Edge Computing Meets Information-Centric Networking

In today’s era of explosion of Internet of Things (IoT) and end-user devices and their data volume, emanating at the network’s edge, the network should be more in-tune with meeting the needs of these demanding edge computing applications. To this end, we design and prototype Information-Centric edge (ICedge), a general-purpose networking framework that streamlines service invocation and improves reuse of redundant computation at the edge. ICedge runs on top of Named-Data Networking, a realization of the Information-Centric Networking vision, and handles the “low-level” network communication on behalf of applications. ICedge features a fully distributed design that: (i) enables users to get seamlessly on-boarded onto an edge network, (ii) delivers application invoked tasks to edge nodes for execution in a timely manner, and (iii) offers naming abstractions and network-based mechanisms to enable (partial or full) reuse of the results of already executed tasks among users, which we call “compute reuse”, resulting in lower task completion times and efficient use of edge computing resources. Our simulation and testbed deployment results demonstrate that ICedge can achieve up to 50× lower task completion times leveraging its networkbased compute reuse mechanism compared to cases, where reuse is not available