EUROSYS

The rapid digitalization across industries comes with many challenges. One key problem is how the ever-growing and volatile data generated at distributed locations can be efficiently processed to inform decision making and improve products. ...

Transmitting data to cloud datacenters in distributed IoT applications introduces significant communication latency, but is often the only feasible solution when source nodes are computationally limited. To address latency concerns, Cloudlets, in-...

With the idea of exploiting all the computational resources that an IoT environment with multiple interconnected devices offers, serverkernel is presented as a new operating system architecture that blends ideas from distributed operating systems, ...

The integrity of operating system (OS) kernels is of paramount importance in order to ensure the secure operation of user-level processes and services as well as the benign behavior of the entire system. Attackers aim to exploit a system's kernel since ...

Edge computing and Federated Learning (FL) can work in tandem to address issues related to privacy and collaborative distributed learning in untrusted IoT environments. However, deployment of FL in resource-constrained IoT devices faces challenges ...

Making deep learning models efficient at inferring nowadays requires training with an extensive number of labeled data that are gathered in a centralized system. However, gathering labeled data is an expensive and time-consuming process, centralized ...

When looking at a building or urban settings, information about the number of people present and the way they move through the space is useful for helping designers to understand what they have created, fire marshals to identify potential safety hazards,...

With edge computing emerging as a promising solution to cope with the challenges of Internet of Things (IoT) systems, there is an increasing need to automate the deployment of large-scale applications along with the publish/subscribe brokers they ...

Activity recognition using deep learning and sensor data can help monitor activities and health conditions of people who need assistance in their daily lives. Deep Neural Network (DNN) models to infer the activities require data collected by in-home ...

Intelligent Personal Assistants (IPAs) such as Apple's Siri, Google Now, and Amazon Alexa are becoming an increasingly important class of web application. In contrast to previous keyword-oriented search applications, IPAs support a rich query interface ...

This paper presents LDP-Fed, a novel federated learning system with a formal privacy guarantee using local differential privacy (LDP). Existing LDP protocols are developed primarily to ensure data privacy in the collection of single numerical or ...

This paper presents EdgeC, a new language for programming reactive distributed applications. It enables separation of concerns between expressing behavior and controlling distributed aspects, inspired by aspect-oriented language design. In EdgeC, ...