Rafael Teixeira , Gabriele Baldoni , Mário Antunes , Diogo Gomes , Rui L. Aguiar
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引用次数: 0
Abstract
Artificial intelligence (AI) is a fundamental pillar in developing next-generation networks. Federated learning (FL) emerges as a promising solution to address data privacy concerns during AI model training within the network. However, training AI models on user equipment raises challenges regarding battery consumption, unreliable connections, and communication overhead. This paper proposes Zenoh, a data-centric communication middleware, as an alternative to the traditional Message Passing Interface (MPI) for FL applications. Zenoh’s decentralized nature and low communication overhead make it suitable for resource-constrained devices and unreliable network connections. The paper compares Zenoh and MPI in a realistic FL scenario, demonstrating Zenoh’s potential to outperform MPI in terms of flexibility, communication efficiency, and system complexity.
期刊介绍:
Computer and Communications networks are key infrastructures of the information society with high socio-economic value as they contribute to the correct operations of many critical services (from healthcare to finance and transportation). Internet is the core of today''s computer-communication infrastructures. This has transformed the Internet, from a robust network for data transfer between computers, to a global, content-rich, communication and information system where contents are increasingly generated by the users, and distributed according to human social relations. Next-generation network technologies, architectures and protocols are therefore required to overcome the limitations of the legacy Internet and add new capabilities and services. The future Internet should be ubiquitous, secure, resilient, and closer to human communication paradigms.
Computer Communications is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and survey papers covering all aspects of future computer communication networks (on all layers, except the physical layer), with a special attention to the evolution of the Internet architecture, protocols, services, and applications.