Deep Learning Aided Intelligent Reflective Surfaces for 6G: A Survey
The envisioned sixth-generation (6G) networks anticipate robust support for diverse
applications, including massive machine-type communications, ultra-reliable low-latency …
applications, including massive machine-type communications, ultra-reliable low-latency …
DELTA: Deadline aware energy and latency-optimized task offloading and resource allocation in GPU-enabled, PiM-enabled distributed heterogeneous MEC …
A Islam, M Ghose - Journal of Systems Architecture, 2025 - Elsevier
The use of Multi-access Edge Computing (MEC) technology holds great potential for
supporting modern, computation-intensive, and time-sensitive applications. These …
supporting modern, computation-intensive, and time-sensitive applications. These …
[HTML][HTML] AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks
Abstract Within the Internet of Things (IoT) ecosystem, the Routing Protocol for Low-Power
and Lossy Networks (RPL) serves as a foundational element for network communication …
and Lossy Networks (RPL) serves as a foundational element for network communication …
SMixSL: The Smashed-Mixture Technique for Split Learning With Localizable Features
In recent years, split learning (SL) with personalized data and region-dropout strategies has
been proposed to enhance the performance of classifier convolutional neural networks …
been proposed to enhance the performance of classifier convolutional neural networks …
[HTML][HTML] Heterogeneity-aware device selection for efficient federated edge learning
Y Shi, J Nie, X Li, H Li - International Journal of Intelligent Networks, 2024 - Elsevier
Federated learning (FL) combined with mobile edge computing (FEEL) provides an end-to-
edge synergetic learning approach to allow end devices to participate in machine learning …
edge synergetic learning approach to allow end devices to participate in machine learning …