Related papers: DNS-based dynamic context resolution for SCHC

LoRaWAN is a prominent communication standard to enable reliable low-power, long-range communications for the Internet of Things (IoT). The modulation technique used in LoRaWAN, commonly known as LoRa modulation, is based on the principle…

6LoWPAN (IPv6 over IEEE 802.15.4) standardized by IEEE 802.15.4 provides IP communication capability for nodes in WSN. An adaptation layer is introduced above the MAC layer to achieve header compression, fragmentation and reassembly of IP…

The DNS is a key component of the Internet. Originally designed to facilitate the resolution of host names to IP addresses, its scope has continuously expanded over the years, today covering use cases such as load balancing or service…

We propose Nephalai, a Compressive Sensing-based Cloud Radio Access Network (C-RAN), to reduce the uplink bit rate of the physical layer (PHY) between the gateways and the cloud server for multi-channel LPWANs. Recent research shows that…

Sentence compression is the task of compressing a long sentence into a short one by deleting redundant words. In sequence-to-sequence (Seq2Seq) based models, the decoder unidirectionally decides to retain or delete words. Thus, it cannot…

Sentence compression is the task of creating a shorter version of an input sentence while keeping important information. In this paper, we extend the task of compression by deletion with the use of contextual embeddings. Different from…

Designing distributed, fast and reliable wireless consensus protocols is instrumental in enabling mission-critical decentralized systems, such as robotic networks in the industrial Internet of Things (IIoT), drone swarms in rescue missions,…

Recent research has focused on applying speech large language model (SLLM) to improve speech emotion recognition (SER). However, the inherently high frame rate in speech modality severely limits the signal processing and understanding…

Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low latency grounded in language instructions. While Video-based Large Language Models (Video-LLMs)…

Several novel industrial applications involve human control of vehicles, cranes, or mobile robots through various high-throughput feedback systems, such as Virtual Reality (VR) and tactile/haptic signals. The near real-time interaction…

Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper, we study how to bridge this gap and go beyond with a novel…

Scaling language models to longer contexts is essential for capturing rich dependencies across extended discourse. However, na\"ive context extension imposes significant computational and memory burdens, often resulting in inefficiencies…

Content-centric networking (CCN) introduces a paradigm shift from a host centric to an information centric communication model for future Internet architectures. It supports the retrieval of a particular content regardless of the physical…

Deep learning has shown impressive performance in semantic segmentation, but it is still unaffordable for resource-constrained mobile devices. While offloading computation tasks is promising, the high traffic demands overwhelm the limited…

In this paper, the proposed methodology for conducting experiments on a small number of devices for evaluating systems with a large number of devices. A software package for assessing the performance of LPWAN (Long Range Wide Area Networks,…

Managing extensive context remains a critical bottleneck for Large Language Models (LLMs), particularly in applications like long-document question answering and autonomous agents where lengthy inputs incur high computational costs and…

Transformer-based language models (LMs) are inefficient in long contexts. We propose Dodo, a solution for context compression. Instead of one vector per token in a standard transformer model, Dodo represents text with a dynamic number of…

Energy consumption of IoT devices is a very important issue. For this reason, many techniques have been developed to allow IoT nodes to be aware of the amount of available energy. When energy is missing, the device halts and saves its…

Caching at small base stations (SBSs) has demonstrated significant benefits in alleviating the backhaul requirement in heterogeneous cellular networks (HetNets). While many existing works focus on what contents to cache at each SBS, an…

Earth observation satellites generate large amounts of real-time data for monitoring and managing time-critical events such as disaster relief missions. This presents a major challenge for satellite-to-ground communications operating under…