mlsanityData to 14 Oct 2026

Towards Traffic Modelling of Multi-Agent Systems: The Role of Coordination Topology

arXiv 2608.20494 ↗First posted 20 Aug 2026cs.NI cs.AI cs.MAcited by 0

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Multi-agent LLM systems are an emerging networked workload whose rapid deployment raises questions about the traffic patterns they generate. Compared to conventional applications, these systems generate requests internally: a single user task can induce a structured sequence of model calls whose timing is governed by coordination logic rather than by user arrival rate. It is not clear whether classical traffic models, designed for human-driven workloads, apply to this setting. We present an empirical characterisation of LLM-call interarrival time distributions across sequential, star, and full-mesh agentic coordination topologies, using a multi-layer measurement framework over 500 repeated runs per topology. We find that topology fundamentally shapes the arrival process of requests to the LLM backend: fan-out coordination introduces a structural bimodality absent in sequential execution, and the reasoningphase component is best described by a log-normal distribution, with the Poisson exponential null model decisively rejected across all topologies. These differences propagate to inference and network level metrics. The framework and analysis pipeline are released openly at https://github.com/dlamagna/agentraffic.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 3 of its 21 references that are in the map. First posted on arXiv 20 Aug 2026.

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3 of 21 references.

References · 3

  1. 2020Internet Traffic Volumes Are Not Gaussian -- They Are Log-Normal: An 18-Year Longitudinal Study With Implications for Modelling and Prediction (Complete Version)cited by 4
  2. 2019On approximate validation of models: A Kolmogorov-Smirnov based approachcited by 3
  3. 2025Introducing Large Language Models as the Next Challenging Internet Traffic Sourcecited by 1

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