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Earlier sources: Networks
This hardware thread follows networks through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗23 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
A Review of Energy-Efficient Routing Protocols for Underwater Acoustic Wireless Sensor Networks ↗
Underwater acoustic sensor networks (UASNs) are key enabling technology for the Internet of Underwater Things (IoUT), supporting environmental monitoring, offshore exploration, disaster warning and surveillance. Existing routing approaches include depth- and hop-by-hop schemes, geographic/vector-based forwarding, clustering, opportunistic and cross-layer routing, and more recent reinforcement-learning and multi-modal designs. Depth-based methods are simple and localization-free but can create redundant forwarding and energy hotspots near sinks; geographic methods provide directional forwarding…
- OpenAlex · Published · First archived
Local Voronoi Computation and Sweep Line Intersection for Efficient Voronoi-Based Grouping Test Localization in Wireless Sensor Networks ↗
Node localization is a fundamental service in wireless sensor networks (WSNs), and range-free schemes such as the Voronoi diagram-based grouping test localization (VTL) achieve good accuracy without distance measurements. However, VTL repeatedly constructs Voronoi diagrams over all anchor nodes of each group and resolves the intersection of positive regions by an exhaustive grid scan, which limits its scalability. This paper proposes and evaluates two optimizations: (1) a local Voronoi computation that restricts the computation to the k anchors nearest to the strongest-signal anchor (including…
- OpenAlex · Published · First archived
Hybrid Multi‐Gateway Authentication Protocol for 6LoWPAN‐Based Marine Wireless Sensor Networks ↗
ABSTRACT This paper proposes a secure and efficient three‐factor authentication scheme to address the security issues in the integration scenario of multi‐gateway wireless sensor networks (WSNs) and 6LoWPAN in marine Internet of Things (IoT). Existing approaches exhibit vulnerabilities to cryptographic breaches, single‐point failures, high computational costs, and inefficient long‐distance transmission in maritime settings. To mitigate these limitations, we integrate blockchain technology, elliptic curve cryptography (ECC), the Chinese Remainder Theorem (CRT), and a dynamic credential update m…
- arXiv · Published · First archived
Toward Intelligent Networks via AI-Aware GPU-Native Packet Processing ↗
The integration of inline Artificial Intelligence (AI) models into critical network infrastructure is fundamentally bottlenecked by the high latency and synchronization overhead of CPU-mediated packet processing. While legacy GPU offload and recent CPU-bypass frameworks attempt to bridge this gap, they remain trapped in proprietary ecosystems or still rely on the host CPU and coarse-grained batching to coordinate stateful telemetry and AI pipeline execution. In this paper, we propose AGP, a novel framework that promotes the GPU from a passive accelerator to a primary data-path controller, answ…
- OpenAlex · Published · First archived
EnCost: uplink-cost-aware cluster-head selection with sink-trajectory look-ahead for energy-efficient mobile-sink wireless sensor networks ↗
In a mobile-sink wireless sensor network (WSN), the cluster-head (CH)-to-sink uplink periodically enters the distance-fourth-power multipath regime, where electing a CH far from the sink incurs a disproportionate energy penalty. We propose EnCost-CR , a closed-form CH-selection rule that scores each node by its residual energy minus the modelled energy of the uplink it would pay as a head, instead of the normalized distance used by existing energy- and distance-aware rules. We are explicit that this is cost accounting carried out before the decision, not prediction: it uses the sink position a…
- OpenAlex · Published · First archived
Optimization of Energy usage in Wireless Sensor Networks ↗
Abstract Distributed Wireless Sensor Network (WSN) longevity is heavily constrained by finite battery reserves and data transmission overhead. Balancing energy conservation with link reliability under dynamic node mobility remains a challenge. This study presents a Stepwise Transmission Power Control ( PROPOSED_TPC / TPC-ON ) mechanism within a low-overhead, flat network architecture. Operating as a reactive, discrete state machine under a terrestrial Two-Ray Ground propagation model, the algorithm dynamically minimizes data transmission power without complex continuous tracking loops. Extensi…
- OpenAlex · Published · First archived
Vision based steering control using convolutional neural networks with latency analysis and microcontroller based actuation ↗
This work presents a real-time vision-based steering control framework in which CNN-based steering inference is performed on a host PC and the resulting commands are transmitted to an Arduino UNO for microcontroller-based servo actuation. Using the SullyChen driving dataset for training, the proposed model predicts continuous steering angles from monocular images and transmits the corresponding commands to a servo motor via serial communication. The system achieves a validation mean absolute error (MAE) of 0.093 and a root mean square error (RMSE) of 0.131, outperforming a shallow CNN baseline…
- OpenAlex · Published · First archived
A UAV object detection and spatial mapping framework integrating enhanced YOLOv7 with graph attention networks ↗
This study proposes a unified UAV perception framework that combines enhanced YOLOv7-based small-object detection with graph attention reasoning and spatial projection. The framework augments conventional single-stage detection with relation-aware context modeling while preserving real-time throughput at an input resolution of 640 × 640 on an NVIDIA RTX 3090 GPU. On VisDrone2019, the proposed method achieves 42.6% mAP@0.5 and 25.8% mAP@0.5:0.95, corresponding to gains of 4.8 and 4.2 percentage points over the YOLOv7 baseline. The corrected projection branch also consistently reduces RMSE acros…
- OpenAlex · Published · First archived
QoS-Aware Energy-Efficient Routing in Wireless Sensor Networks via Multi-Objective Differential Evolution ↗
Wireless Sensor Networks (WSNs) are integral to diverse applications, ranging from environmental monitoring to healthcare systems. However, inherent battery capacity constraints dictate that energy efficiency remains a paramount design criterion. Fulfilling the strict Quality of Service (QoS) demands of modern applications—such as low latency and high reliability—often conflicts with energy conservation objectives. Consequently, unequal energy dissipation among sensor nodes, particularly in the vicinity of the Base Station (BS), frequently induces the critical “energy hole” problem, thereby se…
- OpenAlex · Published · First archived
Adaptive intelligent resource optimization in wireless sensor networks using reinforcement learning and compressive sensing ↗
Abstract In response to the energy and memory limitations of WSNs, this research work introduces a new approach: EMPIRE-CS (Energy and Memory-optimized Performance with Iterative Reinforcement and Compressive Sensing). It is a hybrid approach combining compressive sensing with reinforcement learning and game-theoretic clustering. The architecture supports dynamic cluster head selection, fair energy distribution and effective signal compression with an iterative feedback mechanism between the sensor nodes and the sink. Compressive sensing decreases sampling and storage burdens, while reinforcem…
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How to assess evidence about Networks
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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