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Found 9 papers, 2 papers with code
Data-Driven Latency Probability Prediction for Wireless Networks: Focusing on Tail Probabilities
With the emergence of new application areas, such as cyber-physical systems and human-in-the-loop applications, there is a need to guarantee a certain level of end-to-end network latency with extremely high reliability, e. g., 99. 999%.
Semantically Optimized End-to-End Learning for Positional Telemetry in Vehicular Scenarios
Such a scenario could be illustrated for instance, in vehicular communications where the distance is to be conveyed between a leader and a follower.
The Case for Hierarchical Deep Learning Inference at the Network Edge
Depending on the application, if the inference provided by the local algorithm is incorrect or further assistance is required from large DL models on edge or cloud, only then the ED offloads the data sample.
Online Algorithms for Hierarchical Inference in Deep Learning applications at the Edge
In order to get the best out of both worlds, i. e., the benefits of doing inference on the ED and the benefits of doing inference on ES, we explore the idea of Hierarchical Inference (HI), wherein S-ML inference is only accepted when it is correct, otherwise the data sample is offloaded for L-ML inference.
CLEAVE: Scalable and Edge-native Benchmarking of Networked Control Systems
In this work, we present CLEAVE, a novel, completely software-based framework for repeatable and scalable experimentation in edge native NCSs.
Semantic Communications in Networked Systems: A Data Significance Perspective
We present our vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information for communications and control in networked systems.
Coordinates-based Resource Allocation Through Supervised Machine Learning
Considering that future wireless technologies will be based on dense network deployment, where the mobile terminals are in line-of-sight of the transmitters, the position information of terminals provides an alternative to estimate the channel condition.
On the Minimum Achievable Age of Information for General Service-Time Distributions
There has been a significant research effort in optimizing this metric in communication and networking systems under different settings.
Learning-Based Resource Allocation Scheme for TDD-Based CRAN System
Since, the trajectory of movement for high-mobility users is predictable; therefore, fairly accurate position estimates for those users can be obtained, and can be used for resource allocation to serve the considered users.
