Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

In parallel with the rapid adoption of artificial intelligence (AI) empowered by advances in AI
research, there has been growing awareness and concerns of data privacy. Recent …

As data privacy increasingly becomes a critical societal concern, federated learning has
been a hot research topic in enabling the collaborative training of machine learning models …

Edge computing is an emerging paradigm for the increasing computing and networking
demands from end devices to smart things. Edge computing allows the computation to be …

Federated learning is a privacy-preserving machine learning technique that learns a shared
model across decentralized clients. It can alleviate privacy concerns of personal re …

This paper reviews some of the challenges posed by the huge growth of experimental data
generated by the new generation of large-scale experiments at UK national facilities at the …

Edge computing is the next Internet frontier that will leverage computing resources located
near users, sensors, and data stores to provide more responsive services. Therefore, it is …

Caused by the rising of new network types, eg, Internet of Things (IoT), within the last
decade and related challenges like Big Data and data processing delay, new paradigms …

Implementing edge artificial intelligence (AI) inference and training is challenging with
current memory technologies. As deep neural networks (DNNs) grow in size, this problem is …