#edge computing

36 papers match

cs.CR2026

Designing a GDPR-Compliant Security Architecture for Remote Elderly Care Systems: A Privacy-by-Design Approach

Md. Rahid Parvez, Mikael Soini

The paper proposes the Secure Edge Gateway (SEG), an IoMT security architecture for remote elderly care that combines GDPR‑compliant pseudonymisation, zero‑interaction usability, a…

#gdpr compliance#iot security#elderly care#edge computing
cs.CR2026

Efficient and Privacy Aware Edge Cloud Collaborative Inference for Large Language Models

Yi Li, Cheng Li, Chen Li +2

The paper proposes a privacy‑focused edge‑cloud collaborative framework for large language model inference that authenticates and encrypts KV cache data, allowing lightweight edge…

#edge computing#collaborative inference#large language models#privacy
cs.DC2026

Data Replication Meets Function Scheduling in the Edge-Cloud Continuum

Matteo Cenzato, Dario d'Abate, Arianna Dragoni +2

The paper studies the joint problem of placing replicated data and scheduling serverless functions in edge‑cloud environments under strong and eventual consistency, offering an opt…

#serverless computing#edge computing#data replication#function scheduling
cs.LG2026

Lightweight Multi-Scale Anomaly Detection for Resource-Constrained Edge Devices

Raheen Junaid Wani, Smruti R. Sarangi

The paper introduces a compact multi‑scale autoencoder that uses discrete wavelet transforms to detect anomalies in univariate time‑series data, achieving high accuracy with a mode…

#anomaly detection#time-series analysis#edge computing#autoencoders
eess.IV2026

Improving Autonomous Nano-drones Performance via Automated End-to-End Optimization and Deployment of DNNs

Vlad Niculescu, Lorenzo Lamberti, Francesco Conti +2

The paper presents an automated workflow to train, optimize, and deploy a vision-based CNN (PULP‑Dronet) on an ultra‑low‑power multicore SoC for autonomous navigation of sub‑10 cm…

#nano-drones#deep learning#edge computing#vision-based navigation
cs.CV2026

A Comprehensive Evaluation of Deep Learning Object Detection Models on Heterogeneous Edge Devices

Daghash K. Alqahtani, Muhammad Aamir Cheema, Maria A. Rodriguez +1

The paper benchmarks several deep learning object detection models on various edge devices, measuring accuracy, latency, and energy use while also analyzing performance as scene co…

#object detection#edge computing#benchmarking#energy efficiency