Green Federated Learning: A new era of Green Aware AI

TL;DR

This paper surveys the landscape of Green Federated Learning, emphasizing its potential to create energy-efficient AI solutions for sustainable IoT environments by analyzing existing research and identifying future challenges.

Contribution

It provides a comprehensive analysis of over a hundred FL works focused on green AI, highlighting current issues, challenges, and future directions for sustainable IoT applications.

Findings

Identified key contributions of FL to green AI.

Assessed energy efficiency challenges in FL.

Outlined future research directions for green IoT.

Abstract

The development of AI applications, especially in large-scale wireless networks, is growing exponentially, alongside the size and complexity of the architectures used. Particularly, machine learning is acknowledged as one of today's most energy-intensive computational applications, posing a significant challenge to the environmental sustainability of next-generation intelligent systems. Achieving environmental sustainability entails ensuring that every AI algorithm is designed with sustainability in mind, integrating green considerations from the architectural phase onwards. Recently, Federated Learning (FL), with its distributed nature, presents new opportunities to address this need. Hence, it's imperative to elucidate the potential and challenges stemming from recent FL advancements and their implications for sustainability. Moreover, it's crucial to furnish researchers, stakeholders, and interested parties with a roadmap to navigate and understand existing efforts and gaps in green-aware AI algorithms. This survey primarily aims to achieve this objective by identifying and analyzing over a hundred FL works, assessing their contributions to green-aware artificial intelligence for sustainable environments, with a specific focus on IoT research. It delves into current issues in green federated learning from an energy-efficient standpoint, discussing potential challenges and future prospects for green IoT application research.