# How Can AI be Distributed in the Computing Continuum? Introducing the Neural Pub/Sub Paradigm

arXiv: https://arxiv.org/abs/2309.02058 · HTML: https://mlsanity.com/paper/2309.02058/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Sep 2023.

## Built on by (most cited first, 4 of 4)

- [Large Language Model Based Multi-Agent System Augmented Complex Event Processing Pipeline for Internet of Multimedia Things](https://mlsanity.com/paper/2501.00906/) (2025)
- [Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities](https://mlsanity.com/paper/2312.14647/) (2023)
- [Follow-Me AI: Energy-Efficient User Interaction with Smart Environments](https://mlsanity.com/paper/2404.12486/) (2024)
- [Neural Router: Semantic Content Matching for Agentic AI](https://mlsanity.com/paper/2605.25701/) (2026)

## Abstract (arXiv)

This paper proposes the neural publish/subscribe paradigm, a novel approach to orchestrating AI workflows in large-scale distributed AI systems in the computing continuum. Traditional centralized broker methodologies are increasingly struggling with managing the data surge resulting from the proliferation of 5G systems, connected devices, and ultra-reliable applications. Moreover, the advent of AI-powered applications, particularly those leveraging advanced neural network architectures, necessitates a new approach to orchestrate and schedule AI processes within the computing continuum. In response, the neural pub/sub paradigm aims to overcome these limitations by efficiently managing training, fine-tuning and inference workflows, improving distributed computation, facilitating dynamic resource allocation, and enhancing system resilience across the computing continuum. We explore this new paradigm through various design patterns, use cases, and discuss open research questions for further exploration.