Search Results for author:
Found 5 papers, 4 papers with code
FedLesScan: Mitigating Stragglers in Serverless Federated Learning
We implement our strategy by extending an open-source serverless FL system called FedLess.
IAD: Indirect Anomalous VMMs Detection in the Cloud-based Environment
A fault or an anomaly in the VMM can propagate to the VMs hosted on it and ultimately affect the availability and reliability of the applications running on those VMs.
FedLess: Secure and Scalable Federated Learning Using Serverless Computing
These include rapid scalability, no infrastructure management, automatic scaling to zero for idle clients, and a pay-per-use billing model.
DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices
In this work, we present and compare the performance in terms of inference time and power consumption of the four Systems on a Chip (SoCs): Asus Tinker Edge R, Raspberry Pi 4, Google Coral Dev Board, Nvidia Jetson Nano, and one microcontroller: Arduino Nano 33 BLE, on different deep learning models and frameworks.
Online Memory Leak Detection in the Cloud-based Infrastructures
A memory leak in an application deployed on the cloud can affect the availability and reliability of the application.
