Distributed Computing with Language Models at the Edge: A Framework and Prototype
Journal
International Conference on the Internet of Things (IoT)
Type
conference contribution
Date Issued
2025
Author(s)
Dinesh Kumar Karthikeyan
;
Roopesh Kumar Shanmugasundaram
;
Anna-Sofia Paavonen
;
Tommi Mikkonen
;
Niko Mäkitalo
;
Abstract
The evolution of cyber-physical systems (CPS) necessitates new methods to manage growing complexity and dynamic interactions between physical and digital domains. This paper presents the Edge Multimodal Intelligence Network on Devices (EdgeMIND) – a cognitive edge computing framework to support CPS development. EdgeMIND deploys I/O nodes powered by large language models (LLMs) across heterogeneous edge resources to process multimodal data streams. These nodes perform runtime decision making, enabling context-aware interactions with minimal cloud reliance. The framework generates adaptive outputs by integrating retrieval-augmented generation (RAG) with Situational Awareness (SA) enhanced by topic modeling. Empirical evaluations with three LLMs on edge devices show that SA achieves up to 56% latency reduction in CPU-bound nodes and 50% in GPU-based nodes. It also reduces CPU/GPU utilization, memory usage, and thermal load. These results confirm EdgeMIND’s effectiveness for context-aware, resource-efficient multimodal processing in CPS as demonstrated in a prototype application. EdgeMIND advances the design of intelligent, efficient edge systems for responsive AI-driven services.
Language
English (United States)
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
ACM
Publisher place
New York, USA
Pages
9
Event Title
15th International Conference on the Internet of Things (IoT 2025)
Event Location
Vienna, Austria
Event Date
November 18–21, 2025
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
IoT_2025_EdgeMind.pdf
Size
3.11 MB
Format
Adobe PDF
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