SyncAnyone: Distributed Synchronization Suite

• SyncAnyone is a collection of protocols that ensure reliable state, set, and file reconciliation in highly distributed, dynamic networks using rateless coding and conflict-free merging.
• It integrates deterministic set reconciliation, succinct cryptographic proofs, and synchronous emulation in anonymous networks to address challenges in blockchain, decentralized storage, and multi-filesystem environments.
• The suite achieves near-optimal communication and time overheads, validated through empirical tests on Ethereum networks and theoretical proofs, offering practical solutions for data and filesystem synchronization.

SyncAnyone is a collective designation for a suite of synchronization protocols and algorithmic primitives underpinning reliable state, set, and data reconciliation in highly distributed, dynamic, and heterogeneous network environments. The name surfaces in several distinct but conceptually linked research tracks, notably: deterministic set reconciliation for blockchains using CertainSync/UniverseReduceSync (Keniagin et al., 11 Apr 2025), succinct cryptographic proof exchange for decentralized storage redundancy via SNIPS (Nygaard et al., 2023), simulation of synchronous algorithms in anonymous dynamic networks with κ-Synchronizer (Bazzi et al., 10 Jun 2025), and provably correct near-linear time multi-filesystem merging (Csirmaz et al., 2023). These frameworks address complementary challenges in distributed systems by combining rateless coding, algebraic conflict resolution, efficient set listing, and low-communication correctness guarantees.

1. Rateless Set Reconciliation: CertainSync and UniverseReduceSync

CertainSync is a reconciliation framework targeting the synchronization of unordered object sets (e.g., blockchain mempools, distributed transaction pools) with provable guarantee, zero-parameter adaptivity, and rateless communication (Keniagin et al., 11 Apr 2025). Parties $P_1$, $P_2$ each hold sets $S_1$, $S_2 \subseteq U$ over a (possibly enormous) universe $U$; the symmetric-difference $d = |(S_1\setminus S_2) \cup (S_2 \setminus S_1)|$ is a priori unknown.

Protocol highlights:

• Rateless IBLT construction: Communication proceeds in batches of IBLT cells indexed by rows of a fixed binary mapping matrix $M_{n,d}$. No prediction or estimator of $d$ required. Peeling decoding on the IBLT deterministically lists all $d$ difference-elements if $m \geq m^*(n, d)$, where $m^*(n, d)$ is the minimum number of rows needed for $d$-decodability.
• Information-theoretic bound: Communication achieves the lower limit $\Omega(d\log(U/d))$.
• Universe reduction: For blockchain-scale universes, UniverseReduceSync hashes elements to a reduced universe $[n_r]$, controlling representation length and collision rate $\delta$; remaining collisions are eliminated via a second round.

Empirical validation on Ethereum testnet data shows one-round convergence and complete recovery with dramatically reduced communication versus Graphene, Digest, and rateless IBLT baselines. SyncAnyone leverages these guarantees for P2P/blockchain set-sync operations, recommending protocol variants (EGH, OLS, ExtendedHamming) based on universe and symmetric-difference parameters.

2. Succinct Proof of Storage: SNIPS in Decentralized Redundancy

SNIPS implements a succinct, cryptographically verifiable proof-of-storage mechanism to enable efficient, collision-resistant chunk listing and redundancy maintenance across storage peers (Nygaard et al., 2023).

Core features:

• Signature-augmented MPHF proofs: Each chunk $a$ is mapped to a fresh possession proof $cp_a = H(\eta \| a)$ (nonce-based, collision-resistant); the prover builds a Minimal Perfect Hash Function ($h$) over these, returning $(\eta, [start, end], h)$ plus a digital signature.
• Efficient membership queries: Verifier checks its own chunks against the proof in $O(n)$ time, requiring just $2$–$3.3$ bits per chunk. Missing chunks are indexed directly; collisions are inherently flagged.
• Three-phase protocol: CreateProof, FindMissingChunks, selective Upload of missing data. Empirical evaluation in Ethereum Swarm shows SNIPS reduces metadata traffic by $10^3$-fold compared to Pullsync and amortizes creation/verification to $\sim20\mu$s per chunk.

SyncAnyone incorporates SNIPS as the data-integrity backbone for periodic, peer-driven redundancy checks and chunk restoration within decentralized storage overlays.

3. Deterministic Synchronization in Anonymous Dynamic Networks

κ-Synchronizer ("SyncAnyone") is a generic protocol for emulating synchronous distributed algorithms in networks devoid of unique node identifiers and subject to arbitrary, continuous topology changes (Bazzi et al., 10 Jun 2025).

Model specifics:

• Extended Pull: Each node maintains per-port state (ack/block bits), leverages local disconnection detectors, and hands over multi-writer ports for handshake-based neighborship simulation.
• Phase-based handshake: Synchronization of distributed round advancement via per-phase atomic ack/block exchange, ensuring invariants of consistent graph simulation and state transfer.
• Correctness guarantees: For any synchronous algorithm $A$, κ-Synchronizer produces a per-phase simulated graph $H_i$ matching the synchronous schedule; liveness/termination are proved under weakly-fair activation.
• Compositionality: Existing algorithms (e.g., spanning forests, majority gossip) become semi-synchronously executable with polynomial overhead in $\Delta$ (max degree) and $\log R$ (max rounds).

SyncAnyone thus provides infrastructure for synchronizing algorithms over anonymous and continuously evolving P2P graphs, supporting robust distributed computation.

4. Near-Linear Time Multi-Filesystem Synchronization

The algebraic synchronization suite developed in (Csirmaz et al., 2023) robustly reconciles arbitrarily many filesystem replicas by canonicalization and conflict-free merging.

Key principles:

• Algebraic modeling: Filesystem commands $(n, x, y)$ are composed, inverted, and equivalenced strictly by algebraic properties and tree invariants.
• Canonical set construction: Replica updates are reduced to non-breaking, intention-confined, $\prec_{pc}$-connected command sets; synchronization means finding maximal conflict-free canonical mergers.
• Greedy/nondeterministic merging: Efficient $O(N\log N)$ sort plus $O(N)$ merging yields synchronized state. All conflict classes (same node, parent/child, edit/destructor) are resolved algorithmically; asynchronous sync accommodates local post-request edits.
• Extensions: The framework generalizes to DAG-structured filesystems (supporting links) via equivalence-class canonicalization.

This suite renders SyncAnyone an optimal backend for reliable, asynchronous filesystem merging across offline or divergent replicas in CRDT/OT-style applications.

5. Deterministic Binary File Synchronization under Deletions

A specialized protocol from (Yazdi et al., 2012) achieves error-exponentially reliable reconstruction of a binary file after random deletions, using $O(n\beta\log(1/\beta))$ bits exchanged.

Protocol layers:

• Pivots and segmentation: Source partitions $X$ into alternating segments and pivots, transmitting pivots to the receiver. DAG alignment recovers matching pivot locations, working in polynomial time.
• Edit-recovery: Each segment between matched pivots is synchronized via a one-way edit-synchronization primitive, minimizing additional bits.
• LDPC correction: Remaining errors are removed via systematic LDPC parity bits, achieving overall bit-error probability $2^{-\Omega(n)}$.

This method attains the information-theoretic lower bound for synchronization from deletions and can be adapted as a component of SyncAnyone in file or block streaming contexts.

6. Practical Recommendations and Comparative Analysis

SyncAnyone, as a generalized term for these state-of-the-art protocols, embodies the following best practices:

• Use UniverseReduceSync-EGH for set synchronization over massive universes, tuning collision probability for quick one-round convergence at low communication cost.
• Deploy SNIPS for storage or redundancy synchronization wherever chunk integrity and proof size are paramount.
• Apply κ-Synchronizer for distributed state/membership maintenance in anonymous, highly dynamic networks.
• Employ algebraic reconciliation for multi-replica filesystem or CRDT merging, supporting links and DAGs natively.
• Leverage the deterministic binary sync protocol for sparse edit channels and streaming data with random deletions.

Across baselines, SyncAnyone-affiliated algorithms consistently avoid parameter estimation, offer rateless operation, minimize risk of failure in reconciliation or listing, and achieve optimal or near-optimal communication, time, and space overheads. Empirical and theoretical assessments confirm their efficacy in blockchain, decentralized storage, anonymous networking, and distributed filesystem synchronization scenarios.