Related papers: DNS-based dynamic context resolution for SCHC
Deep neural networks (DNNs) have inspired new studies in myriad edge applications with robots, autonomous agents, and Internet-of-things (IoT) devices. However, performing inference of DNNs in the edge is still a severe challenge, mainly…
This article presents a novel framework for real-time Light Detection and Ranging (LiDAR) data transmission that leverages rate-adaptive technologies and point cloud encoding methods to ensure low-latency, and low-loss data streaming. The…
Minimal infrastructure requirements make LoRa suitable for service delivery in remote areas. Additionally, web applications have become a de-facto standard for modern service delivery. However, Long Range (LoRa) fails to enable HTTP access…
We propose to employ a recently developed IoT-based wireless technology, so called low-power wide-area networks (LPWANs), to exploit their long range, low power, and inherent compatibility to cloud storage and computing. We create a…
In the sentence classification task, context formed from sentences adjacent to the sentence being classified can provide important information for classification. This context is, however, often ignored. Where methods do make use of…
Fast data synchronization in wireless ad hoc networks is a challenging and critical problem. It is fundamental for efficient information fusion, control and decision in distributed systems. Previously, distributed data synchronization was…
Spectrum sensing is an essential component of modern wireless networks as it offers a tool to characterize spectrum usage and better utilize it. Deep Learning (DL) has become one of the most used techniques to perform spectrum sensing as…
With increasing density and heterogeneity in unlicensed wireless networks, traditional MAC protocols, such as carrier-sense multiple access with collision avoidance (CSMA/CA) in Wi-Fi networks, are experiencing performance degradation. This…
This paper studies a sequential task offloading problem for a multiuser mobile edge computing (MEC) system. We consider a dynamic optimization approach, which embraces wireless channel fluctuations and random deep neural network (DNN) task…
With network requirements diverging across emerging applications, latency-critical services demand minimal logic delay, while hyperscale training and collectives require sustained line-rate throughput for synchronized bulk transfers. This…
To reduce the storage requirements, remote sensing (RS) images are usually stored in compressed format. Existing scene classification approaches using deep neural networks (DNNs) require to fully decompress the images, which is a…
In this work, we propose a novel hybrid method for scene text detection namely Correlation Propagation Network (CPN). It is an end-to-end trainable framework engined by advanced Convolutional Neural Networks. Our CPN predicts text objects…
In order to break through the development bottleneck of modern wireless communication networks, a critical issue is the out-of-date channel state information (CSI) in high mobility scenarios. In general, non-stationary CSI has statistical…
This paper presents a context key/value compression method for Transformer language models in online scenarios, where the context continually expands. As the context lengthens, the attention process demands increasing memory and…
With the advent of 5G networks and the rise of the Internet of Things (IoT), Content Delivery Networks (CDNs) are increasingly extending into the network edge. This shift introduces unique challenges, particularly due to the limited cache…
We propose a neural network model for contextual regression in which the regression model depends on contextual features that determine the active submodel and an algorithm to fit the model. The proposed simple contextual neural network…
Vehicles shipping sensors for onboard systems are gaining connectivity. This enables information sharing to realize a more comprehensive understanding of the environment. However, peer communication through public cellular networks brings…
Content-Centric Networking (CCN) research addresses the mismatch between the modern usage of the Internet and its outdated architecture. Importantly, CCN routers may locally cache frequently requested content in order to speed up delivery…
Both IEEE 802.15.4 and 802.15.4a standards allow for dynamic channel allocation and use of multiple channels available at their physical layers but its MAC protocols are designed only for single channel. Also, sensor's transceivers such as…
The deployment of LoRaWAN (Long Range Wide Area Network) in dynamic environments, such as smart campuses, presents significant challenges in optimizing network parameters like spreading factor (SF), transmission power (TxPower), and…