SoK: DAG-based Consensus Protocols

Mayank Raikwar; Nikita Polyanskii; Sebastian M\"uller

REVIEW 2 major objections 5 minor 121 references

SoK: DAG-based Consensus Protocols

T0 review · 2 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read This SoK argues that DAG-based consensus protocols are best understood through a CAP-theorem-inspired trade-off between availability and consistency, and it sorts the field into two families accordingly: availability-focused protocols…

desk verdict Useful SoK with a genuinely new availability/consistency taxonomy, but the binary classification is undermined by its own duplicate entry for Slipstream and needs a clarifying revision before it becomes a stable reference. read the letter →

arxiv 2411.10026 v2 pith:SJZM4U57 submitted 2024-11-15 cs.DC

Mayank Raikwar , Nikita Polyanskii , Sebastian Müller This is my paper · ORCID

classification cs.DC

keywords DAG-basedconsensusblockDAGCAPtheoremByzantinefaulttolerancedistributedledgertechnologyavailability-focusedprotocolsconsistency-focusedbroadcastprimitives

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This systematization of knowledge claims that the design of DAG-based consensus protocols is governed by the same trade-off captured in the CAP theorem: a protocol can emphasize availability or consistency, but not both. It divides the protocols into availability-focused and consistency-focused families, then subdivides them by DAG structure and by whether block dissemination uses optimistic best-effort broadcast or reliable, certified broadcast. The paper maps each protocol to its participation model, network assumptions, ordering guarantees, finality type, and known attack vectors, and it identifies research gaps such as standardized benchmarks, formal security proofs, fairness, and mempool design. A reader would care because DAG-based ledgers are a major candidate for scalable, low-latency consensus, and this paper provides a structured way to compare their otherwise heterogeneous designs.

What carries the argument

The organizing device is the CAP-theorem-inspired dichotomy itself, which the paper uses to split protocols into availability-focused and consistency-focused categories. The second load-bearing mechanism is the blockDAG: a directed acyclic graph in which each block references multiple predecessors via hash links, establishing causal order and enabling parallel block production, unlike a linear blockchain. Within the two families, the central distinguishing machinery is the broadcast primitive: best-effort broadcast for optimistic DAGs versus reliable or consistent broadcast for certified DAGs, with the certified case making every block a certificate signed by a quorum of validators. The paper maps concepts such as finality, leader-based or leaderless consensus, mempool structure, and network model onto these categories, making the taxonomy the analytical engine of the survey.

What would settle it

Finding a documented DAG-based consensus protocol that combines open, dynamically available participation with deterministic finality and no BFT-style quorum certificates, and that therefore fits neither the availability-focused nor the consistency-focused description, would refute the classification's completeness. A formal counterexample showing that the consistency-safety and availability-liveness correlations cannot be instantiated together in any DAG protocol would similarly undermine the CAP-inspired framing.

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Extended reading notes

Core claim

The paper's central claim is that every DAG-based consensus protocol can be classified by which side of the availability-versus-consistency trade-off it prioritizes. Availability-focused protocols, further split into structured DAGs and unstructured DAGs, aim to keep the ledger making progress through lottery-based block proposal, often in permissionless and dynamically available settings, and they typically offer probabilistic finality. Consistency-focused protocols, split into optimistic DAGs and certified DAGs, build on Byzantine fault tolerant agreement, typically in permissioned settings, and they offer deterministic finality. The paper further argues that the choice of broadcast primitive is a defining design decision: best-effort broadcast underlies optimistic DAGs and requires mechanisms to handle equivocation, while reliable or consistent broadcast underlies certified DAGs and represents each block as a quorum-signed certificate. It also surveys the attack vectors that matter for each family, including balance attacks, parasite-chain attacks, equivocation attacks, liveness attacks, censorship, fork bombs, and data-availability attacks, and it discusses desirable properties such as ordering, fairness, MEV protection, and garbage collection.

Load-bearing premise

The classification assumes that the CAP theorem is a meaningful lens for DAG-based consensus and that consistency can be informally equated with safety while availability is equated with liveness; if that mapping fails in permissionless or quasi-permissionless settings, the two-category split loses its grounding.

Editorial extensions

If this is right

Designers can locate a protocol by the trade-off it accepts: availability-focused DAGs sacrifice deterministic ordering for continuous progress, while consistency-focused DAGs sacrifice openness for deterministic finality.
The subcategories map onto implementation choices: optimistic DAGs rely on best-effort broadcast and must handle equivocation, whereas certified DAGs sign every block with a quorum certificate and gain stronger consistency guarantees.
Attack surfaces divide by category: availability-focused protocols are more exposed to balance and parasite-chain attacks, while consistency-focused protocols face liveness, equivocation, and censorship risks.
For payment-only applications, partial ordering from the DAG is sufficient, so total ordering is not an unavoidable cost in such systems.
The paper's research gaps point to concrete next steps: standardized benchmark suites, generalized security abstractions, mempool designs that prevent transaction duplication, and fairness and MEV analyses for open writing access.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

The CAP-inspired divide is an instrumental ordering device rather than a proven theorem; the paper does not derive the two classes from first principles, so the taxonomy is best read as a map of the field rather than a law of nature.
The availability/consistency axis could be combined with the broadcast-primitive axis to make testable predictions: optimistic-DAG families should show lower common-case latency but weaker equivocation resistance than certified-DAG families, a comparison that a common benchmark could settle.
Because the paper deliberately excludes performance evaluation, the classification cannot currently predict which family achieves higher throughput; running the surveyed protocols on a shared benchmark would test whether the taxonomy correlates with measured trade-offs.
The identified research gaps, especially standardized benchmarks and formal security proofs, suggest that the next synthesis of DAG consensus is likely to be empirical rather than purely taxonomic.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

The paper is worth reading and worth refereeing. It is a real systematization: the two-axis split (availability- vs consistency-focused, with structured/unstructured and optimistic/certified subcategories) is not in the earlier surveys it cites, and it organizes a fast-growing literature in a way that lets you locate protocols and open problems quickly. The authors are also honest in the right places: footnote 2 flags that finality claims are unverified, footnote 3 flags uncertain network-model assignments, and Section I.C explicitly disclaims performance evaluation even though the abstract promises it. That last mismatch is real and should be fixed, but it is cosmetic compared with the classification issue.

The soft spot is the Slipstream entry. Table II lists Slipstream in both the availability-focused (unstructured DAG) and consistency-focused (optimistic DAG) columns. The paper's own description of Slipstream says it is an ebb-and-flow protocol with an optimistic ordering that is live under a sleepy model and a final ordering that is safe in eventual lock-step synchrony. That is precisely a protocol that refuses the binary trade-off. The paper nowhere defines a hybrid category or says the two classes may overlap, so the central classification is not a partition. This is not a fatal flaw, but it is the kind of thing a serious referee should push on: either add a hybrid/overlap label, or justify why ebb-and-flow protocols get split. Meshcash, also ebb-and-flow, is placed only in the availability column, which makes the Slipstream duplicate look like an oversight rather than a deliberate modeling choice.

The CAP mapping is likewise informal, and the paper says so. That is acceptable for a survey, but the informality means the taxonomy should be read as a heuristic lens, not a theorem. The attack-vector table and the discussion of desirable properties (fairness, MEV, garbage collection) are useful additions, and the self-citations (Tangle 2.0, Slipstream, the fairness paper) involve protocols that anchor the taxonomy; that is a mild burden, not a disqualifier, because the descriptions match the cited work as far as I can tell.

Bottom line: this is a solid, useful survey with one internal inconsistency that needs resolving. It deserves peer review, and I would cite it once the Slipstream issue is addressed. Worth bringing to the reading group if anyone works on DAG consensus or survey methodology.

Referee Report

2 major / 5 minor

Summary. This SoK surveys DAG-based consensus protocols and organizes them around a CAP-inspired availability/consistency dichotomy. After introducing background concepts (ordering, ledger model, participation, network model, dynamic availability, broadcast primitives, adversarial model, finality), the paper categorizes protocols in Table II into availability-focused (structured/unstructured DAG) and consistency-focused (optimistic/certified DAG) families. It then reviews attack vectors, desirable properties such as fairness and MEV protection, recent developments, and future research directions. The paper states in Section I.C that it does not present performance evaluations, and it flags unverified finality claims and uncertain network classifications in footnotes 2 and 3.

Significance. If the classification were made internally consistent, this would be a useful reference for researchers entering DAG-based consensus: the coverage is broad and current (through 2024), the tables (Tables I–III) condense a large literature, and the paper is transparent about its limitations. The explicit disclaimers about unverified finality claims and uncertain network models are commendable for a systematization. The paper does not provide formal proofs, machine-checked artifacts, or reproducible code, but those are not required for a SoK. However, the central contribution is the availability/consistency taxonomy, and that taxonomy currently contains a concrete internal inconsistency that must be fixed before the paper can serve as a reliable reference.

major comments (2)

[Sec. III, introductory paragraph] The binary classification is internally falsified by the duplicate listing of Slipstream under both Availability-Focused Unstructured DAG and Consistency-Focused Optimistic DAG. Section III-B describes Slipstream as an ebb-and-flow protocol [54] that offers an optimistic ordering live in a sleepy model under up to 50% Byzantine faults and a final ordering safe in an eventual lock-step synchronous model under up to 33% Byzantine faults; ebb-and-flow protocols [75] exist precisely to combine dynamic availability with deterministic finality. Slipstream therefore satisfies both category criteria from Section III simultaneously. Meshcash, also described as ebb-and-flow in Section III-B, is listed only under availability-focused, which suggests the placement is not being applied by a consistent rule. The paper nowhere defines a hybrid category or states that membership can be non-exclusive, while Section I.C promises 'a structured classification ... into Availability-focused and Consistency-focused categories.' The taxonomy as presented is not a partition. The authors should either introduce a hybrid category (including at least Slipstream and Meshcash) or explicitly state that the two categories are non-exclusive and provide guidance for classifying mixed protocols.
[Sec. III] The CAP-based motivation is load-bearing for the classification, but the paper states only an informal correlation of consistency with safety and availability with liveness, while acknowledging these terms are 'traditionally distinct concepts.' Because the subsequent category definitions rely on notions such as dynamic availability, permissionless settings, BFT primitives, and permissioned environments rather than on a formal CAP interpretation, it is unclear whether the availability/consistency labels are derived from the CAP lens or retrofitted onto protocol families. The authors should either make the mapping precise (for example, define availability-focused as satisfying liveness under dynamically available participation and consistency-focused as satisfying deterministic safety under BFT quorum assumptions) or explicitly frame the taxonomy as a pragmatic, non-formal heuristic and engage with known critiques of applying CAP to permissionless/dynamically available systems. As written, the informal mapping contributes to the ambiguous placement of hybrid protocols such as Slipstream.

minor comments (5)

[Abstract vs. Sec. I.C] The abstract states that the paper analyzes 'performance and trade-offs' of DAG-based protocols, but the note in Section I.C says 'the paper does not discuss or present any performance evaluation of the included protocols.' The abstract should be revised to avoid this overclaim, or the note should be moved to a more prominent position.
[Sec. VI.D] The sentence ending 'Lin et al. developed TangleSim [113] ... Byzantine environments. Bullshark [47].' leaves a dangling citation 'Bullshark [47].' that appears to be a leftover fragment; complete the sentence or remove the dangling reference.
[Sec. III.B] In 'The Slipstream protocol, [54], is also ebb-and-flow style consensus protocol [75]', the indefinite article 'a' is missing before 'ebb-and-flow'.
[Reference [66]] The author name 'E. G /dieresis.ts1un Sirer' appears corrupted; it should read 'E. Gün Sirer'.
[Sec. I.B.4] The 'Reachability challenge' bullet is vague; it would benefit from a concrete example, such as how pruning or light-client operation depends on reachability information in the DAG.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the paper is a taxonomy, not a derivation; self-citations are not load-bearing.

full rationale

I found no circular step that reduces a prediction or derived result to its own inputs. The paper is a Systematization of Knowledge: its central claim is a classification of DAG-based consensus protocols into availability-focused and consistency-focused categories (Sec. III, Table II), which is a taxonomic organization rather than a derivation. The categories are defined by design attributes (lottery-based open participation vs. BFT-style permissioned/quasi-permissionless consensus), and protocols are assigned to them by descriptive analysis. There are no fitted parameters, no equations, and no quantitative prediction; the paper explicitly disclaims performance evaluation. The CAP-theorem framing is an external lens, and the paper itself flags that it informally correlates consistency with safety and availability with liveness (Sec. III). Self-citations appear (Tangle 2.0 [17], Slipstream [54], Fairness Notions [94], and related IOTA papers), but they are used as objects of classification or as literature references, not as evidence that forces the taxonomy; the cited protocols are independently published and externally verifiable. The duplicate listing of Slipstream in both the availability-focused Unstructured DAG column and the consistency-focused Optimistic DAG column of Table II is an internal consistency problem for the binary partition, and Tangle 2.0 is discussed under availability-focused protocols in Sec. III-B but tabulated under consistency-focused protocols, yet overlap or misclassification is not a circular reduction. Footnote 2 acknowledges that finality results are claims by protocol authors, further showing the paper is reporting rather than deriving. The only minor concern is nontrivial self-citation in the set of protocols anchoring the taxonomy, but it is not load-bearing, so the circularity score is 2.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

The paper postulates that CAP theorem's consistency/availability/partition tolerance framing transfers to DAG-based consensus (Section III intro) and that the protocols partition cleanly into the proposed categories; Table II's duplicate listing of Slipstream shows the second postulate is not fully satisfied. No free parameters or invented entities are introduced.

assumptions (2)

domain assumption CAP theorem provides a valid lens for analyzing DAG-based consensus protocols, with consistency mapped to safety and availability mapped to liveness.
Invoked in Section III intro to justify the binary classification; the paper itself notes the mapping is informal.
domain assumption DAG-based consensus protocols can be cleanly partitioned into availability-focused and consistency-focused categories (with subcategories).
This is the paper's central thesis; Table II contradicts it by listing Slipstream under both Availability-focused Unstructured DAG and Consistency-focused Optimistic DAG.

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Cite this review

Pith. "Pith review of SoK: DAG-based Consensus Protocols." pith.science (2026). https://pith.science/paper/SJZM4U57

@misc{pith2026241110026,
  author       = {Pith},
  title        = {Pith review of: SoK: DAG-based Consensus Protocols},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SJZM4U57}},
  note         = {Machine review of arXiv:2411.10026}
}

read the original abstract

This paper is a Systematization of Knowledge (SoK) on Directed Acyclic Graph (DAG)-based consensus protocols, analyzing their performance and trade-offs within the framework of consistency, availability, and partition tolerance inspired by the CAP theorem. We classify DAG-based consensus protocols into availability-focused and consistency-focused categories, exploring their design principles, core functionalities, and associated trade-offs. Furthermore, we examine key properties, attack vectors, and recent developments, providing insights into security, scalability, and fairness challenges. Finally, we identify research gaps and outline directions for advancing DAG-based consensus mechanisms.

Figures

Figures reproduced from arXiv: 2411.10026 by the authors.

**Figure 1.** Blockchain and blockDAG framework where multiple blocks can be added concurrently, supporting parallel processing of transactions. By diverging from the sequential constraints of traditional models, DAGbased protocols offer improved scalability and flexibility in transaction processing. B. Why a DAG-based Consensus Protocol In the pursuit of transcending the inherent trade-off between security and performance and i… view at source ↗

**Figure 2.** The evolution of DAG-based consensus protocols over [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗

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Reference graph

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