The carbon footprint of software activities is determined by embodied and operational
emissions of hardware resources. This paper presents cMemento, a concept that enables …

The Meltdown and Spectre hardware vulnerabilities shocked hardware manufacturers and
system users upon discovery. Numerous attack vectors and mitigations have been …

Background segment cleaning in log-structured file system has a significant impact on
mobile devices. A low triggering frequency of the cleaning activity cannot reclaim enough …

The recent advances of hardware-based accelerators for machine learning—in particular
neural networks—attracted the attention of embedded-systems designers and engineers …

The widespread integration of the Internet of Things (IoT) into daily operations has made
optimizing energy consumption in low-power edge devices increasingly important. This is …

Machine learning has shown tremendous success in a large variety of applications. The
evolution of machine-learning applications from cloud-based systems to mobile and …

The recent restructuring of the electricity grid (ie, smart grid) introduces a number of
challenges for today's large-scale computing systems. To operate reliable and efficient …

This chapter shows methods for the resource-optimized design of AI functionality for edge
devices powered by microprocessors or microcontrollers. The goal is to identify Pareto …

Many system-level management and optimization techniques need accurate estimates of
power consumption and performance. Earlier research has proposed many high …

Estimating execution time is a crucial task during the development of safety-critical
embedded systems. Processor simulation or emulation tools on various abstraction levels …