IRS: An Incentive-compatible Reward Scheme for Algorand

TL;DR

This paper introduces a game-theoretic reward scheme for Algorand, enhancing node participation incentives while ensuring protocol security and efficiency through Bayesian game modeling and real-world scenario analysis.

Contribution

It proposes a novel incentive-compatible reward scheme for Algorand, modeled as a Bayesian game, with conditions ensuring equilibrium participation even with malicious adversaries.

Findings

The reward scheme incentivizes honest participation.

Protocol overheads are manageable in real-world scenarios.

Necessary conditions for equilibrium are derived.

Abstract

Founded in 2017, Algorand is one of the world's first carbon-negative, public blockchains inspired by proof of stake. Algorand uses a Byzantine agreement protocol to add new blocks to the blockchain. The protocol can tolerate malicious users as long as a supermajority of the stake is controlled by non-malicious users. The protocol achieves about 100x more throughput compared to Bitcoin and can be easily scaled to millions of nodes. Despite its impressive features, Algorand lacks a reward-distribution scheme that can effectively incentivize nodes to participate in the protocol. In this work, we study the incentive issue in Algorand through the lens of game theory. We model the Algorand protocol as a Bayesian game and propose a novel reward scheme to address the incentive issue in Algorand. We derive necessary conditions to ensure that participation in the protocol is a Bayesian Nash equilibrium under our proposed reward scheme even in the presence of a malicious adversary. We also present quantitative analysis of our proposed reward scheme by applying it to two real-world deployment scenarios. We estimate the costs of running an Algorand node and simulate the protocol to measure the overheads in terms of computation, storage, and networking.