Introduction to federated learning systems

Syed Zawad, Feng Yan, Ali Anwar

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

In this chapter, we introduce federated learning from a systems perspective. We go into the details of the different federated learning scenarios that have different system design considerations. We first introduce two most common but quite different federated learning scenarios, namely cross-device federated learning and cross-silo federated learning. Cross-device federated learning typically involves a significant number of parties (e.g., thousands to millions), who are usually less reliable and equipped with mobile or IoT devices that have various computing and communication capabilities. In cross-silo federated learning, the parties are usually a small number of organizations with ample computing power and reliable communications. We first describe the two very different problems that each of them address. We then describe the architectural differences between the two and their corresponding training steps. We also discuss the unique systems challenges that arise due to these properties and give a brief description of current works that have talked about these problems in detail.

Original languageEnglish (US)
Title of host publicationFederated Learning
Subtitle of host publicationA Comprehensive Overview of Methods and Applications
PublisherSpringer International Publishing
Pages195-212
Number of pages18
ISBN (Print)9783030968960
DOIs
StatePublished - Jul 7 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

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