The increasing functional and nonfunctional requirements of real-time applications, the
advent of mixed criticality computing, and the necessity of reducing costs are leading to an …

Machine learning inference is becoming a core building block for interactive web
applications. As a result, the underlying model serving systems on which these applications …

Distributed systems are pervasive nowadays, being found in different areas, from smart toys
to smart factories. As the usage of such systems increases, so does their complexity and …

Many modern computing systems must provide reliable latency with minimal energy. Two
central challenges arise when allocating system resources to meet these conflicting …

We present the first lock-free implementation of an extensible hash table running on current
architectures. Our algorithm provides concurrent insert, delete, and find operations with an …

Embedded real-time systems must meet timing constraints while minimizing energy
consumption. To this end, many energy optimizations are introduced for specific platforms or …

This article focuses on mixed-criticality applications with functions that have different timing
requirements, ie, hard real-time (HRT), soft real-time (SRT), and functions that are not time …

The study focuses on developing a unified approach to define information specificities for
key performance indicators (KPIs). Borrowing from the time-system theory, the paper defines …

An increasing number of software applications incorporate runtime Deep Neural Networks
(DNNs) to process sensor data and return inference results to humans. Effective deployment …

Deterministic networking has recently drawn much attention by investigating deterministic
flow scheduling. Combined with artificial intelligent (AI) technologies, it can be leveraged as …