YAIFS: Yet (not) Another Intelligent Fog Simulator: A Framework for Agent-Driven Computing Continuum Modeling & Simulation

2026-04-21

AI Summary

This work proposes a hierarchical, service-oriented fog computing simulation framework that addresses the limited interactivity of traditional distributed system simulators, which hinders agent-driven dynamic experimentation and real-time intervention. For the first time, the framework integrates the Model Context Protocol (MCP) into simulation systems, enabling unified APIs for observability, controllability, and programmability of the simulated environment. It supports heterogeneous agents in dynamically influencing simulations through natural language or collaborative interactions, combining large language model (LLM) integration, multi-agent coordination, and runtime resource scheduling to establish an AI-driven, adaptive experimental paradigm. Empirical evaluations demonstrate the effectiveness of LLM-powered assistants in exerting natural language control over simulations and showcase the capability of multi-agent systems to achieve efficient, adaptive regulation under dynamic workloads.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Simulation plays a key role in the design and evaluation of distributed systems, yet it is often treated as a static tool with limited interaction capabilities. In this work, we present Yet (not) Another Intelligent Fog Simulator (YAIFS), and evolution of YAFS that redefines simulation as an interactive, service-oriented environment. YAIFS introduce a layered architecture that exposes the simulation through a unified API and service interface, enabling external entities to observe, control, and modify its execution. A central contribution is the integration of the Model Context Protocol (MCP) as a standardized interaction layer between agents and the simulation. Through MCP, heterogeneous agents can access state, invoke actions and coordinate behavior using a common set of tools, decoupling agent experimentation workflows. We illustrate these capabilities through two scenarios: an LLM-based assistant that enable natural language control of simulations, and a multi-agent setting where agents monitor system conditions and adapt placement decisions at runtime. These scenarios demonstrate how MCP structures agent-simulation interaction and enable adaptive behavior under dynamic workloads. The proposed approach transforms simulation into an interactive and programmable environment, opening new directions for AI-driven experimentation in cloud-edge systems. The implementation is publicly available at: http://github.com/acsicuib/YAIFS

Problem

• simulation
• agent-driven computing
• interactive simulation
• Model Context Protocol
• fog computing

Innovation

• Model Context Protocol
• agent-driven simulation
• fog computing
• interactive simulation
• computing continuum