[Paper] Hypergraph based Multi-Party Payment Channel

Source: arXiv - 2512.11775v1

Overview

The paper proposes Hypergraph‑based Multi‑Party Payment Channels (H‑MPCs), a novel off‑chain scaling primitive that replaces the traditional pairwise payment channels with hyperedges funded collectively by multiple participants. By doing so, H‑MPCs eliminate the liquidity fragmentation and channel depletion problems that plague existing payment channel networks (PCNs), while also removing the need for a central coordinator or leader. The authors demonstrate the design on a 150‑node testbed, achieving a ~94 % transaction success rate without relying on HTLC expiries or routing failures.

Key Contributions

• Hypergraph abstraction for PCNs – Introduces hyperedges that represent a shared liquidity pool among any number of parties, enabling flexible routing across multiple participants.
• Leaderless concurrent payments – Designs a proposer‑ordered Directed Acyclic Graph (DAG) update mechanism that allows multiple intra‑ and inter‑hyperedge payments to be processed in parallel without a single point of failure.
• Verifiable state transitions – Provides cryptographic proofs (e.g., aggregated signatures, Merkle proofs) that any participant can independently verify the correctness of a DAG update.
• Robust implementation & evaluation – Implements H‑MPC on a realistic 150‑node network, showing a 94 % success rate and dramatically reduced payment failures compared with classic HTLC‑based PCNs.
• Compatibility layer – Shows how H‑MPC can interoperate with existing bilateral channels, allowing gradual migration for existing blockchain ecosystems.

Methodology

1. Modeling the network as a hypergraph – Nodes are participants, hyperedges are multi‑party channels funded by the union of participants’ balances.
2. State representation – Each hyperedge maintains a balance vector (one entry per participant) stored off‑chain. Updates are expressed as transactions that modify this vector.
3. Proposer‑ordered DAG – When a participant wants to pay, they broadcast a proposal containing the intended balance changes. Other participants validate the proposal locally and, if valid, append it to a shared DAG. The DAG’s topological order guarantees that conflicting updates are never applied simultaneously.
4. Verification & finality – Once a proposal reaches a quorum (e.g., > 2/3 of the hyperedge members), participants generate an aggregated signature that serves as a compact proof of acceptance. The signed DAG node is then committed as the new hyperedge state.
5. Inter‑hyperedge routing – Payments that need to traverse multiple hyperedges are split into atomic sub‑transactions, each handled by its own DAG. The proposer orders these sub‑transactions so that the overall payment either fully succeeds or aborts atomically.
6. Evaluation setup – The authors deployed a simulated blockchain backbone (Ethereum‑style) and a 150‑node overlay network. They compared H‑MPC against a baseline HTLC‑based PCN under varying transaction loads and network latencies.

Results & Findings

Key takeaways

• Liquidity fragmentation is dramatically reduced because a single hyperedge’s pool can be tapped by any participant, eliminating the “dead‑end” channels that block routing.
• Leaderless design removes single‑point‑of‑failure risks; the system continues to operate even if a subset of participants go offline.
• DAG ordering enables high concurrency without sacrificing consistency, leading to higher throughput and lower latency.

Practical Implications

• For blockchain developers – H‑MPC offers a drop‑in replacement for bilateral channels in existing Layer‑2 SDKs, requiring only a modest change to the channel management layer (i.e., handling hyperedge state and DAG propagation).
• For DeFi platforms – Multi‑party liquidity pools can be created on‑the‑fly, allowing users to share collateral across many counterparties, which can lower capital costs for high‑frequency traders and arbitrage bots.
• For payment‑focused applications – Services like micropayment streaming, gaming micro‑transactions, or IoT device payments can benefit from the near‑instant finality and high success rates, reducing the need for fallback on‑chain settlements.
• For network operators – The leaderless architecture simplifies node management and improves resilience; operators can run lightweight “validator” nodes that only need to verify DAG signatures rather than maintain a full channel state.
• Interoperability – Since H‑MPC can coexist with traditional channels, a gradual rollout is possible, letting existing ecosystems adopt the hypergraph model without a hard fork.

Limitations & Future Work

• Scalability of verification – While aggregated signatures reduce proof size, the verification cost grows linearly with the number of participants in a hyperedge; extremely large hyperedges may become a bottleneck.
• Dynamic membership – The current design assumes a relatively static participant set per hyperedge; handling frequent joins/leaves (e.g., churn in a public network) requires additional protocol layers.
• Economic incentives – The paper sketches a fee model but does not provide a formal game‑theoretic analysis of how participants are incentivized to act as proposers or to lock liquidity.
• Security analysis under adversarial network conditions – More extensive testing against Byzantine attacks (e.g., selective message dropping, double‑spending attempts) is left for future work.

Future research directions include optimizing signature aggregation for massive hyperedges, designing robust membership‑change protocols, integrating formal incentive mechanisms, and extending the hypergraph model to cross‑chain payment scenarios.

Authors

• Ayush Nainwal
• Atharva Kamble
• Nitin Awathare

Paper Information

• arXiv ID: 2512.11775v1
• Categories: cs.DC, cs.CR, cs.NI
• Published: December 12, 2025
• PDF: Download PDF