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Executing distributed cyber-physical software processes on edge devices that maintains the resiliency of the overall system while adhering to resource constraints is quite a challenging trade-off to consider for developers. Current…
The continued need for improvements in accuracy, throughput, and efficiency of Deep Neural Networks has resulted in a multitude of methods that make the most of custom architectures on FPGAs. These include the creation of hand-crafted…
This paper introduces OneClock, a generic approach for using time in networked applications. OneClock provides two basic time-triggered primitives: the ability to schedule an operation at a remote host or device, and the ability to receive…
Network log data analysis plays a critical role in detecting security threats and operational anomalies. Traditional log analysis methods for anomaly detection and root cause analysis rely heavily on expert knowledge or fully supervised…
In the context of the Internet of Things (IoT), reliable and energy-efficient provision of IoT applications has become critical. Equipping IoT systems with tools that enable a flexible, well-performing, and automated way of monitoring and…
It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and monitor users. Often, though, these tools assume to access the…
The EU DataGrid project workpackage 4 has as an objective to provide the necessary tools for automating the management of medium size to very large computing fabrics. At the end of the second project year subsystems for centralized…
Autonomous 6G network management requires agents that can execute tools, observe the resulting state changes, and adapt their decisions accordingly. Existing benchmarks based on static questions or scripted episode replay, however, do not…
Effective resource utilisation monitoring and highly granular yet adaptive measurements are prerequisites for a more efficient Grid scheduler. We present a suite of measurement applications able to monitor per-process resource utilisation,…
This paper describes the ATLAS production tool AtCom (for ATLAS Commander). The purpose of the tool is to automate as much as possible the task of a production manager: defining and submitting jobs in large quantities, following up upon…
High energy physics detectors can be described hierarchically from the different subsystems to their divisions in r, phi, theta and to the individual readout channels. An identification schema that follows the logical decomposition of the…
The electrical grid consists of legacy systems that were built with no security in mind. As we move towards the Industry 4.0 area though, a high-degree of automation and connectivity provides: 1) fast and flexible configuration and updates…
The Alpha Magnetic Spectrometer (AMS) is constantly exposed to harsh condition on the ISS. As such, there is a need to constantly monitor and perform adjustments to ensure the AMS operates safely and efficiently. With the addition of the…
The smart grid vision is to revitalize the electric power network by leveraging the proven sensing, communication, control, and machine learning technologies to address pressing issues related to security, stability, environmental impact,…
We describe a framework and tool specification that represents a step towards cybersecurity testing and monitoring of IoT ecosystems. We begin with challenges from a previous paper and discuss an integrated approach and tools to enable…
Power system simulation workflows remain expert-intensive. Engineers must translate study intents into code or API calls, execute analyses, and interpret outputs. To automate this workflow, this paper presents PFAgent, a tractable and…
LLM-based agents have recently attracted significant attention due to their ability to autonomously invoke relevant tools to accomplish complex tasks. However, recent studies have shown that these agents face severe security risks, which…
AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers without a machine learning background. We present the AI Toolkit plugin for JetBrains…
Internet of Things (IoT) systems continuously collect a large amount of data from heterogeneous "smart objects" through standardised service interfaces. A key challenge is how to use these data and relevant event logs to construct…
Stream-based monitoring is a well-established runtime verification approach which relates input streams, representing sensor readings from the monitored system, with output streams that capture filtered or aggregated results. In such…