  Online federated learning (OFL) and online transfer learning (OTL) are two
collaborative paradigms for overcoming modern machine learning challenges such
as data silos, streaming data, and data security. This survey explored OFL and
OTL throughout their major evolutionary routes to enhance understanding of
online federated and transfer learning. Besides, practical aspects of popular
datasets and cutting-edge applications for online federated and transfer
learning are highlighted in this work. Furthermore, this survey provides
insight into potential future research areas and aims to serve as a resource
for professionals developing online federated and transfer learning frameworks.
