Unifying MQTT, CoAP, AMQP & STOMP, MAPS Messaging brings real-time data routing to smart cities & industrial IoT—no firmware changes needed. Built for the connected future. Learn more: mapsmessaging.io!
#IndustrialIoT #ProtocolBridging #MQTT #CoAP #AMQP #STOMP #EdgeIoT

M‑DSL selects workers with a non‑i.i.d. degree metric, delivering higher accuracy and lower communication overhead for edge IoT swarm learning. Read more: https://getnews.me/multi-worker-selection-boosts-distributed-swarm-learning-for-edge-iot/ #edgeiot #ml

Need your edge devices (CoAP) to speak to MQTT systems? MAPS Messaging bridges both protocols with real-time, secure translation—perfect for hybrid IoT networks. Efficient edge. Scalable cloud. One solution.
#CoAPtoMQTT #MAPSMessaging #IoTBridge #Middleware #EdgeIoT

various IoT devices, is vulnerable to attacks from malicious entities that may inject harmful data into the learning process. This paper introduces a new attack method targeting federated learning in EdgeIoT, known as data-independent model [3/6 of https://arxiv.org/abs/2504.10067v1]

arXiv:2504.10067v1 Announce Type: new
Abstract: EdgeIoT represents an approach that brings together mobile edge computing with Internet of Things (IoT) devices, allowing for data processing close to the data source. Sending source data to a server is [1/6 of https://arxiv.org/abs/2504.10067v1]

Kai Li, Shuyan Hu, Bochun Wu, Sai Zou, Wei Ni, Falko Dressler: Undermining Federated Learning Accuracy in EdgeIoT via Variational Graph Auto-Encoders https://arxiv.org/abs/2504.10067 https://arxiv.org/pdf/2504.10067 https://arxiv.org/html/2504.10067