Carbon: Scaling Trusted Payments with Untrusted Machines
Martina Camaioni, Rachid Guerraoui, Jovan Komatovic, Matteo Monti,, Pierre-Louis Roman, Manuel Vidigueira, Gauthier Voron

TL;DR
Carbon is a scalable, high-throughput payment system that enables asynchronous, consensus-free transactions with dynamic validator sets, leveraging untrusted brokers to achieve unprecedented performance in geo-distributed environments.
Contribution
It introduces a novel asynchronous, stake-less voting mechanism and an efficient Byzantine broadcast protocol that together enable high-performance, trustless payments at scale.
Findings
Achieves 1 million payments per second in geo-distributed settings
Outperforms existing systems by three orders of magnitude in throughput
Maintains low latency comparable to state-of-the-art systems
Abstract
This paper introduces Carbon, a high-throughput system enabling asynchronous (safe) and consensus-free (efficient) payments and votes within a dynamic set of clients. Carbon is operated by a dynamic set of validators that may be reconfigured asynchronously, offering its clients eclipse resistance as well as lightweight bootstrap. Carbon offers clients the ability to select validators by voting them in and out of the system thanks to its novel asynchronous and stake-less voting mechanism. Carbon relies on an asynchronous and deterministic implementation of Byzantine reliable broadcast that uniquely leverages a permissionless set of untrusted servers, brokers, to slash the cost of client authentication inherent to Byzantine fault tolerant systems. Carbon is able to sustain a throughput of one million payments per second in a geo-distributed environment, outperforming the state of the art…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPeer-to-Peer Network Technologies · Cloud Computing and Resource Management · Distributed systems and fault tolerance
