In recent years the research community has accumulated overwhelming evidence for the
emergence of complex and heterogeneous connectivity patterns in a wide range of …

One of the most striking properties of the Internet is its flexibility to accommodate features it
was not conceived for. Among the most significant examples, in this survey we consider the …

Abstract Machine learning over distributed data stored by many clients has important
applications in use cases where data privacy is a key concern or central data storage is not …

Cloud Computing: Theory and Practice, Third Edition provides students and IT professionals
with an in-depth analysis of the cloud from the ground up. After an introduction to network …

Federated learning is a distributed machine learning approach for computing models over
data collected by edge devices. Most importantly, the data itself is not collected centrally, but …

Distributed Systems Page 1 DS 2006; Ch1 16-Jan-06 Timo Alanko, 2006 1 Distributed
Systems Spring 2006 Timo Alanko 16-Jan-06 2 Sources of material • Tanenbaum, van …

The key features of peer-to-peer (P2P) systems are scalability and dynamism. The
evaluation of a P2P protocol in realistic environments is very expensive and difficult to …

When I was appointed Director of Education for the Computer Science department at VU
University, I became partly responsible for revitalizing our CS curriculum. At that point in …

In conventional PKI, CAs are assumed to be fully trusted. However, in practice, CAs'
absolute responsibility for providing trustworthiness caused major security and privacy …

The Dutch Advanced School for Computing and Imaging has built five generations of a 200-
node distributed system over nearly two decades while remaining aligned with the shifting …