In recent years, as the boundaries of computing have expanded with the emergence of the
Internet of Things (IoT) and its increasing number of devices continuously producing flows of …

Time-Sensitive Networking (TSN) has been recognized as one of the key enabling
technologies for Industry 4.0 and has been deployed in many mission-and safety-critical …

Federated learning (FL) involves training a model over massive distributed devices, while
keeping the training data localized and private. This form of collaborative learning exposes …

The growing popularity of microservices has led to the proliferation of online cloud service-
based applications, which are typically modelled as Directed Acyclic Graphs (DAGs) …

Network operators and researchers constantly search for platforms to evaluate future
deployments and test new research ideas. When experimenting, they usually face …

Location-based services (LBS) have been significantly developed and widely deployed in
mobile devices. It is also well-known that LBS applications may result in severe privacy …

Web applications rely heavily on software caches to achieve low-latency, high-throughput
services. To adapt to changing workloads, three types of learned caches (learned evictions) …

Mobile phones, wearable devices, and other sensors produce every day a large amount of
distributed and sensitive data. Classical machine learning approaches process these large …

We present Dinomo, a novel key-value store for disaggregated persistent memory (DPM).
Dinomo is the first key-value store for DPM that simultaneously achieves high common-case …

Website fingerprinting (WF) attacks allow an adversary to associate a website with the
encrypted traffic patterns produced when accessing it, thus threatening to destroy the client …