The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained
devices at the edge of the network for efficient deployment of latency-critical and bandwidth …

With the miniaturization of electronics, receivers are getting more and more embedded into
devices with harsh energy constraints. This process has led to new signal processing …

Recent advancements in hardware and software systems have been driven by the
deployment of emerging smart health and mobility applications. These developments have …

The rapid growth of demanding applications in domains applying multimedia processing
and machine learning has marked a new era for edge and cloud computing. These …

The challenging deployment of compute-intensive applications from domains such as
Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of …

Task offloading with Mobile-Edge Computing (MEC) is envisioned as a promising technique
to prolong battery lifetime and enhance the computational capacity of mobile devices. In this …

As modern 5G systems are being deployed, researchers question whether they are sufficient
for the oncoming decades of technological evolution. Growing numbers of interconnected …

The unprecedented progress in computational technologies led to a substantial proliferation
of artificial intelligence applications, notably in the era of big data and IoT devices. In the …

This paper explores the integration and application of Approximate Computing (AxC)
approaches to Machine Learning (ML), especially Deep Learning (DL) models. We focus on …

With the rapid increase in the number of network access devices and the volume of network
access data currently, the shortcomings of the centralized computing architecture …