Usable Agent Discovery for Decentralized AI Systems

Emanuele Carlini; Matteo Mordacchini; Patrizio Dazzi; Saul Urso

arxiv: 2604.23080 · v1 · submitted 2026-04-25 · 💻 cs.MA · cs.AI· cs.DC

Usable Agent Discovery for Decentralized AI Systems

Patrizio Dazzi , Emanuele Carlini , Matteo Mordacchini , Saul Urso This is my paper

Pith reviewed 2026-05-08 07:09 UTC · model grok-4.3

classification 💻 cs.MA cs.AIcs.DC

keywords decentralized AIagent discoverypeer-to-peer overlayschurn resiliencestructured overlaysgossip protocolsKademliamulti-agent systems

0 comments

The pith

Structured overlays handle node churn better in AI agent discovery, while gossip-based ones gain when agent readiness dominates.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines decentralized discovery for software agents in large AI systems spread across many hosts. These agents and their host nodes both experience churn, from failures and departures at the node level and from activation or state changes at the agent level. Simulations compare a structured overlay (Kademlia) against a gossip-based one (Cyclon plus Vicinity) across stable, node-churn, agent-churn, and combined conditions. The results show structured designs maintain better routing efficiency and resilience when nodes churn, whereas gossip approaches stay competitive and often faster when quick access to ready agents matters most. This clarifies which overlay fits different deployment patterns.

Core claim

In agentic systems where nodes host multiple agents, discovery must manage node-level churn from failures and departures alongside agent-level churn from demand-driven warm and cold state switches. Under this two-level churn, Kademlia as a structured overlay provides higher routing efficiency and resilience in stable and node-churn regimes. Cyclon combined with Vicinity as a gossip baseline remains competitive overall and can deliver faster discovery when agent readiness is the primary factor. The interaction of the two churn types reshapes the classic trade-off between structured and unstructured overlays.

What carries the argument

Two-level churn model combining node departures with agent warm/cold state changes, used to compare Kademlia structured overlay against Cyclon+Vicinity gossip overlay across efficiency, resilience, and readiness metrics.

If this is right

Structured overlays maintain lower lookup latency and higher resilience when node failures occur frequently.
Gossip-based overlays reduce discovery time when many agents frequently switch between warm and cold states.
The preferred overlay type shifts depending on whether node churn or agent state changes dominate the workload.
Both overlay families support usable discovery but exhibit clear regime-specific strengths.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Developers could monitor observed churn rates in production to select or switch overlays dynamically.
The two-level churn distinction may guide discovery design in other multi-entity distributed systems such as edge devices or microservices.
Real-world validation would require testing these overlays inside live AI agent platforms rather than simulations alone.

Load-bearing premise

The simulated two-level churn models and chosen baseline overlays accurately reflect real decentralized AI deployments, and the measured metrics capture the main practical trade-offs.

What would settle it

Live measurements from an actual deployed decentralized AI agent system showing that gossip overlays consistently outperform structured ones under high node churn, or that structured overlays remain slower under readiness-dominant workloads.

Figures

Figures reproduced from arXiv: 2604.23080 by Emanuele Carlini, Matteo Mordacchini, Patrizio Dazzi, Saul Urso.

**Figure 1.** Figure 1: Conceptual model of decentralized agent discovery under two-level churn. overlays showed how unstructured neighborhoods can be shaped toward skill similarity without global indexes [2, 6, 1]. More recently, the Internet of AI Agents perspective and continuum-oriented orchestration work have reinforced the need to evaluate discovery jointly with service-level objectives and distributed operating condition… view at source ↗

**Figure 2.** Figure 2: Latency/overhead trade-off across the main operating regimes. steep cost: dense gossip on the unstructured side and aggressive republishing on the structured side both increase background traffic far more than they improve latency or useful discovery quality. The practical lesson is therefore not simply that maintenance matters, but that the two overlay families move along very different cost-quality front… view at source ↗

**Figure 3.** Figure 3: Maintenance vs request-plane cost. stable node churn mild node churn moderate node churn aggressive cooling mild cooling moderate cooling aggressive combined mild combined moderate combined aggressive combined reduced-scale 0.0 0.5 1.0 Success rate Kademlia Cyclon+Vicinity view at source ↗

**Figure 4.** Figure 4: Success rate across regimes. availability reveals when routing quality still converts into usable service view at source ↗

**Figure 5.** Figure 5: Useful availability U∆ vs budget ∆. severe failures under combined instability are more consistent with stale routing than with a generic lack of host-belief freshness. Taken together, these findings support the central claim of the paper: structured and unstructured discovery cannot be ranked by a single scalar notion of “better.” In our evaluation, Kademlia is systematically stronger on success and ofte… view at source ↗

**Figure 6.** Figure 6: p95 latency and overhead from specialists to generalists view at source ↗

**Figure 7.** Figure 7: Targeted maintenance probe with 95% confidence intervals. Kademlia Cyclon+Vicinity 0.00 0.25 0.50 0.75 1.00 Reference Kademlia Cyclon+Vicinity Host Belief Focus Kademlia Cyclon+Vicinity 0.00 0.25 0.50 0.75 1.00 Routing Focus Kademlia Cyclon+Vicinity Dense Gossip Rescue Success Stale Routing Rate Stale Host Belief Rate view at source ↗

**Figure 8.** Figure 8: Targeted staleness diagnostics with 95% confidence intervals. 6 Conclusions and Next Steps We treat decentralized discovery as a problem under two-level churn. By separating node instability from agent readiness, we show structured and unstructured overlays occupy different regimes rather than yielding a single winner. Discovery must be evaluated on lookup efficiency, robustness, and readiness together. … view at source ↗

read the original abstract

Large-scale agentic systems run on distributed infrastructures where many software agents share physical hosts and are discovered via peer-to-peer mechanisms. Discovery must handle node-level churn from failures and host departures and agent-level churn from demand-driven activation, deactivation, and state changes. Their interaction reshapes classic trade-offs between structured and unstructured overlays. We study decentralized agent discovery under this two-level churn, assuming nodes host multiple agents, overlays are structured or gossip-based, and agents switch between warm and cold states. Using Kademlia as a structured and Cyclon+Vicinity as a gossip baseline, we compare stable, node-churn-only, agent-cooling-only, and combined regimes to see when routing efficiency, resilience, and service readiness align or favor different designs. Structured overlays are more robust and efficient in stable and node-churn regimes, while gossip-based overlays remain competitive and can be faster when readiness dominates.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper frames agent discovery under node and agent churn but its simulation comparisons rest on unexamined assumptions about model fidelity.

read the letter

The key takeaway is that this paper tests how well structured and gossip overlays handle agent discovery when both hosts and agents churn, but the simulation setup needs more transparency to make the regime comparisons convincing. It brings the two-level churn idea to the table, where node departures mix with agents going warm or cold based on demand. Using Kademlia and Cyclon+Vicinity as baselines, they look at stable, node-only, agent-only, and combined cases to see impacts on routing, resilience, and readiness. The paper does well in identifying that classic trade-offs change under this combined churn, and it gives a clear structure for when one type might be preferable. The focus on usable discovery for decentralized AI is timely given the rise of agent systems. The main concern is that without details on the churn parameters, how warm/cold transitions affect the overlays, or the exact metrics, it's difficult to assess if the findings hold. The stress-test note is on point here: real deployments might have correlated churn or different activation patterns that aren't captured, potentially flipping the results on robustness versus speed. Readers working on P2P mechanisms for multi-agent AI would find this relevant as an initial exploration. It could spark ideas for their own designs, though anyone relying on it for decisions should replicate the experiments with their specific workloads. Overall, the paper shows clear thinking on the problem and engages with relevant literature on overlays, so it deserves a serious referee. I would send it for review and ask for fuller experimental reporting and perhaps some real-world trace validation.

Referee Report

2 major / 2 minor

Summary. The manuscript studies decentralized agent discovery in large-scale AI systems where nodes host multiple agents and experience two-level churn: node-level churn from failures and departures, and agent-level churn from demand-driven warm/cold state transitions. It compares a structured overlay (Kademlia) to a gossip-based baseline (Cyclon+Vicinity) across stable, node-churn-only, agent-cooling-only, and combined regimes, evaluating routing efficiency, resilience, and service readiness. The central claim is that structured overlays are more robust and efficient under stable and node-churn conditions, while gossip-based overlays remain competitive and can be faster when readiness dominates.

Significance. If the simulation-based comparisons are reproducible and the two-level churn model is faithful to real deployments, the work could help designers choose between structured and unstructured overlays for agentic systems. The multi-regime analysis is a positive feature, but the absence of experimental details prevents assessing whether the reported trade-offs would persist outside the simulated setting.

major comments (2)

[Abstract] Abstract: The abstract reports regime-specific performance differences from simulations but supplies no quantitative details on the two-level churn model (node departure rates, agent cooling probabilities, or correlation between node and agent events), the precise definition of the 'readiness' metric, or the simulation parameters (node count, lookup workloads, or statistical tests). These omissions are load-bearing because the headline claim that 'gossip-based overlays can be faster when readiness dominates' rests entirely on the fidelity of this model and metric.
[Evaluation] Evaluation section (or equivalent): The manuscript does not describe how agent warm/cold state transitions are reflected in routing-table maintenance or lookup success for either Kademlia or Cyclon+Vicinity, nor does it report sensitivity analysis on the independent two-level churn assumption. If real deployments exhibit bursty or correlated churn, the claimed advantages of structured overlays in node-churn regimes could reverse, undermining the central comparison.

minor comments (2)

[Abstract] The abstract introduces 'service readiness' without a formal definition or formula; adding this in the main text would clarify what favors the gossip baseline.
No mention of reproducibility artifacts (code, parameter files, or raw data) is present; including these would strengthen the empirical contribution.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed feedback on our manuscript. We appreciate the emphasis on making the abstract and evaluation sections more self-contained and transparent. We address each major comment below and indicate the revisions we will make to the next version of the paper.

read point-by-point responses

Referee: [Abstract] Abstract: The abstract reports regime-specific performance differences from simulations but supplies no quantitative details on the two-level churn model (node departure rates, agent cooling probabilities, or correlation between node and agent events), the precise definition of the 'readiness' metric, or the simulation parameters (node count, lookup workloads, or statistical tests). These omissions are load-bearing because the headline claim that 'gossip-based overlays can be faster when readiness dominates' rests entirely on the fidelity of this model and metric.

Authors: We agree that the abstract would be strengthened by incorporating a small number of key quantitative anchors so that the central claims can be evaluated at a glance. In the revised manuscript we will expand the abstract to include the simulation scale (node count and number of lookup workloads), a concise definition of the readiness metric, and a brief characterization of the two-level churn parameters. The complete specifications of the churn model, including departure rates, cooling probabilities, correlation assumptions, and the statistical procedures used, are already presented in Sections 3 and 5; the abstract revision will simply surface the most salient values without altering the paper's length constraints. revision: yes
Referee: [Evaluation] Evaluation section (or equivalent): The manuscript does not describe how agent warm/cold state transitions are reflected in routing-table maintenance or lookup success for either Kademlia or Cyclon+Vicinity, nor does it report sensitivity analysis on the independent two-level churn assumption. If real deployments exhibit bursty or correlated churn, the claimed advantages of structured overlays in node-churn regimes could reverse, undermining the central comparison.

Authors: We accept that the current description of how agent state transitions interact with overlay maintenance and lookup procedures can be made more explicit. We will add a dedicated paragraph in the Evaluation section that details the concrete mechanisms: for Kademlia, cold agents are excluded from routing buckets and trigger lookup retries or failures; for Cyclon+Vicinity, gossip exchanges and vicinity sets are restricted to warm agents. In addition, we will include a new sensitivity-analysis subsection that reports results under correlated churn (node departures that increase the probability of simultaneous agent cooling). These additions will directly address the concern about potential reversal of advantages when the independence assumption does not hold. revision: yes

Circularity Check

0 steps flagged

Empirical simulation comparison with no circular derivations or self-referential reductions

full rationale

The paper conducts an empirical study comparing structured (Kademlia) and gossip-based (Cyclon+Vicinity) overlays under simulated two-level churn regimes (node and agent). Central claims rest on simulation outcomes for routing efficiency, resilience, and readiness across stable, node-churn, agent-cooling, and combined scenarios. No equations, fitted parameters renamed as predictions, self-definitional constructs, or load-bearing self-citations appear in the provided abstract or description. Baselines are standard and externally established; results do not reduce to inputs by construction. This is a standard empirical evaluation whose validity hinges on simulation fidelity rather than any definitional or citation-chain circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Relies on standard domain assumptions about P2P overlays and churn without introducing new free parameters or invented entities.

axioms (2)

domain assumption Nodes host multiple agents that can switch between warm and cold states
Explicitly stated as part of the study setup in the abstract.
domain assumption Overlays are either structured (Kademlia) or gossip-based (Cyclon+Vicinity)
Chosen as baselines for the comparison.

pith-pipeline@v0.9.0 · 5457 in / 1145 out tokens · 37308 ms · 2026-05-08T07:09:42.658441+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

18 extracted references · 18 canonical work pages

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Journal of Computer and System Sciences79, 291–308 (2013)

Baraglia, R., Dazzi, P., Mordacchini, M., Ricci, L.: A peer-to-peer recommender system for self-emerging user communities based on gossip overlays. Journal of Computer and System Sciences79, 291–308 (2013)

work page 2013

[2] [2]

In: Balandin, S., Koucheryavy, Y., Hu, H

Baraglia, R., Dazzi, P., Mordacchini, M., Ricci, L., Alessi, L.: Group: A gossip based building community protocol. In: Balandin, S., Koucheryavy, Y., Hu, H. (eds.) Smart Spaces and Next Generation Wired/Wireless Networking, Lecture Notes in Computer Science, vol. 6869, pp. 496–507. Springer (2011)

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In: 2009 International Confer- ence on Ultra Modern Telecommunications & Workshops (ICUMT)

Carlini, E., Coppola, M., Laforenza, D., Dazzi, P., Martinelli, S., Ricci, L.: Service and resource discovery supports over p2p overlays. In: 2009 International Confer- ence on Ultra Modern Telecommunications & Workshops (ICUMT). pp. 1–8. IEEE (2009)

work page 2009

[4] [4]

Frontiers in High Performance Computing1, 1164915 (2023)

Carlini, E., Coppola, M., Dazzi, P., Ferrucci, L., Kavalionak, H., Korontanis, I., Mordacchini, M., Tserpes, K.: Smartorc: Smart orchestration of resources in the compute continuum. Frontiers in High Performance Computing1, 1164915 (2023)

work page 2023

[5] [5]

Dazzi, P.: The internet of ai agents (iaia): A new frontier in networked and dis- tributed intelligence. Int. J. Netw. Distrib. Comput.13, 16 (2025)

work page 2025

[6] [6]

In: 2011 11th IEEE Int

Dazzi, P., Mordacchini, M., Baglini, F.: Experiences with complex user profiles for approximate p2p community matching. In: 2011 11th IEEE Int. Conf. Comput. Inf. Technol. (CIT). pp. 53–58. IEEE Computer Society (2011)

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Communications of the ACM56(2), 74–80 (2013)

Dean, J., Barroso, L.A.: The tail at scale. Communications of the ACM56(2), 74–80 (2013)

work page 2013

[8] [8]

In: Proceedings of the Annual ACM Symposium on Principles of Distributed Computing (PODC)

Demers, A., Greene, D., Hauser, C., Irish, W., Larson, J.: Epidemic algorithms for replicated database maintenance. In: Proceedings of the Annual ACM Symposium on Principles of Distributed Computing (PODC). pp. 1–12 (1987)

work page 1987

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Computer37(5), 60–67 (2004)

Eugster, P.T., Guerraoui, R., Kermarrec, A.M., Massoulié, L.: Epidemic informa- tion dissemination in distributed systems. Computer37(5), 60–67 (2004)

work page 2004

[10] [10]

IEEE Access 12, 19229–19249 (2024)

Ferrucci, L., Mordacchini, M., Dazzi, P.: Decentralized replica management in latency-bound edge environments for resource usage minimization. IEEE Access 12, 19229–19249 (2024)

work page 2024

[11] [11]

Journal of Computer and System Sciences82(7), 1161–1179 (2016)

Ferrucci,L.,Ricci,L.,Albano,M.,Baraglia,R.,Mordacchini,M.:Multidimensional range queries on hierarchical voronoi overlays. Journal of Computer and System Sciences82(7), 1161–1179 (2016)

work page 2016

[12] [12]

ACM Trans

Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.M., van Steen, M.: Gossip- based peer sampling. ACM Trans. Comput. Syst.25(3), 8:1–8:36 (2007) Usable Agent Discovery for Decentralized AI Systems 13

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Jonas, E., Schleier-Smith, J., Sreekanti, V., Tsai, C.C., Khandelwal, A., Pu, Q., Shankar, V., Carreira, J., Krauth, K., Yadwadkar, N., Gonzalez, J.E., Popa, R.A., Stoica, I.: Cloud programming simplified: A berkeley view on serverless computing. Tech. Rep. UCB/EECS-2019-3, University of California, Berkeley (2019)

work page 2019

[14] [14]

In: Proceedings of the International Workshop on Peer-to-Peer Systems (IPTPS)

Maymounkov,P.,Mazières,D.:Kademlia:Apeer-to-peerinformationsystembased on the xor metric. In: Proceedings of the International Workshop on Peer-to-Peer Systems (IPTPS). pp. 53–65 (2002)

work page 2002

[15] [15]

The agntcy agent directory service: Architecture and implementation,

Muscariello, L., Pandey, V., Polic, R.: The agntcy agent directory service: Archi- tecture and implementation. arXiv preprint arXiv:2509.18787 (2025)

work page arXiv 2025

[16] [16]

In: Proceedings of the ACM SIGCOMM Conference

Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S.: A scalable content- addressable network. In: Proceedings of the ACM SIGCOMM Conference. pp. 161–172 (2001)

work page 2001

[17] [17]

In: Proceedings of the ACM SIGCOMM Conference

Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup protocol for internet applications. In: Proceedings of the ACM SIGCOMM Conference. pp. 149–160 (2001)

work page 2001

[18] [18]

In: European Conference on Parallel Processing

Voulgaris, S., Van Steen, M.: Epidemic-style management of semantic overlays for content-based searching. In: European Conference on Parallel Processing. pp. 1143–1152. Springer (2005)

work page 2005