Zhonghui Ge (Shanghai Jiao Tong University), Yi Zhang (Shanghai Jiao Tong University), Yu Long (Shanghai Jiao Tong University), Dawu Gu (Shanghai Jiao Tong University)

A leading approach to enhancing the performance and scalability of permissionless blockchains is to use the payment channel, which allows two users to perform off-chain payments with almost unlimited frequency. By linking payment channels together to form a payment channel network, users connected by a path of channels can perform off-chain payments rapidly. However, payment channels risk encountering fund depletion, which threatens the availability of both the payment channel and network. The most recent method needs a cycle-based channel rebalancing procedure, which requires a fair leader and users with rebalancing demands forming directed cycles in the network. Therefore, its large-scale applications are restricted.

In this work, we introduce Shaduf, a novel non-cycle off-chain rebalancing protocol that offers a new solution for users to shift coins between channels directly without relying on the cycle setting. Shaduf can be applied to more general rebalancing scenarios. We provide the details of Shaduf and formally prove its security under the Universal Composability framework. Our prototype demonstrates its feasibility and the experimental evaluation shows that Shaduf enhances the Lighting Network performance in payment success ratio and volume. Moreover, our protocol prominently reduces users’ deposits in channels while maintaining the same amount of payments.

View More Papers

Drivers and Passengers Maybe the Weakest Link in the...

Aiping Xiong (Pennsylvania State University), Zekun Cai (Pennsylvania State University) and Tianhao Wang (University of Virginia)

Read More

Towards a TEE-based V2V Protocol for Connected and Autonomous...

Mohit Kumar Jangid (Ohio State University) and Zhiqiang Lin (Ohio State University)

Read More

Speeding Dumbo: Pushing Asynchronous BFT Closer to Practice

Bingyong Guo (Institute of Software, Chinese Academy of Sciences), Yuan Lu (Institute of Software Chinese Academy of Sciences), Zhenliang Lu (The University of Sydney), Qiang Tang (The University of Sydney), jing xu (Institute of Software, Chinese Academy of Sciences), Zhenfeng Zhang (Institute of Software, Chinese Academy of Sciences)

Read More

Demo #5: Disclosing the Pringles Syndrome in Tesla FSD...

Zhisheng Hu (Baidu), Shengjian Guo (Baidu) and Kang Li (Baidu)

Read More