Offchain networks emerge as a promising solution to address the scalability challenge of blockchain. Participants directly make payments through a network of payment channels without the overhead of committing onchain transactions. Routing is critical to the performance of offchain networks. Existing solutions use either static routing with poor performance or dynamic routing with high overhead to obtain the dynamic channel balance information. In this paper, we propose Flash, a new dynamic routing solution that leverages the unique characteristics of transactions in offchain networks to strike a better tradeoff between path optimality and probing overhead. By studying the traces of real offchain networks, we find that the payment sizes are heavy-tailed, and most payments are highly recurrent. Flash thus differentiates the treatment of elephant payments from mice payments. It uses a modified max-flow algorithm for elephant payments to find paths with sufficient capacity, and strategically routes the payment across paths to minimize the transaction fees. Mice payments are directly sent by looking up a routing table with a few precomputed paths to reduce probing overhead. Testbed experiments and data-driven simulations show that Flash improves the success volume of payments by up to 2.3x compared to the state-of-the-art routing algorithm.
The above routing algorithms fall into static routing, which does not consider payment channel dynamics and leads to poor throughput performance. Revive @cite_24 and Spider @cite_14 take the dynamic channel balances into consideration and propose centralized offline routing algorithms to maximize the throughput or success volume of payments. As we discussed centralized schemes have high probing overhead and do not work for decentralized offchain networks.
@cite_24 @cite_14
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Scaling the transaction throughput of decentralized blockchain ledgers such as Bitcoin and Ethereum has been an ongoing challenge. Two-party duplex payment channels have been designed and used as building blocks to construct linked payment networks, which allow atomic and trust-free payments between parties without exhausting the resources of the blockchain. Once a payment channel, however, is depleted (e.g., because transactions were mostly unidirectional) the channel would need to be closed and re-funded to allow for new transactions. Users are envisioned to entertain multiple payment channels with different entities, and as such, instead of refunding a channel (which incurs costly on-chain transactions), a user should be able to leverage his existing channels to rebalance a poorly funded channel. To the best of our knowledge, we present the first solution that allows an arbitrary set of users in a payment channel network to securely rebalance their channels, according to the preferences of the channel owners. Except in the case of disputes (similar to conventional payment channels), our solution does not require on-chain transactions and therefore increases the scalability of existing blockchains. In our security analysis, we show that an honest participant cannot lose any of its funds while rebalancing. We finally provide a proof of concept implementation and evaluation for the Ethereum network. With the growing usage of Bitcoin and other cryptocurrencies, many scalability challenges have emerged. A promising scaling solution, exemplified by the Lightning Network, uses a network of bidirectional payment channels that allows fast transactions between two parties. However, routing payments on these networks efficiently is non-trivial, since payments require finding paths with sufficient funds, and channels can become unidirectional over time blocking further transactions through them. Today's payment channel networks exacerbate these problems by attempting to deliver all payments atomically. In this paper, we present the Spider network, a new packet-switched architecture for payment channel networks. Spider splits payments into transaction units and transmits them over time across different paths. Spider uses congestion control, payment scheduling, and imbalance-aware routing to optimize delivery of payments. Our results show that Spider improves the volume and number of successful payments on the network by 10-45 and 5-40 respectively compared to state-of-the-art approaches.