Tit-for-Token: Understanding Fairness when Forwarding Data by Incentivized Peers in Decentralized Storage Networks

TL;DR

This paper introduces Tit-for-Token, a framework to analyze fairness in incentivized decentralized storage networks, considering altruism, reciprocity, and monetary rewards, with extensive simulations demonstrating improved income fairness.

Contribution

The paper develops Tit-for-Token, a novel framework that models fairness in incentivized storage networks, incorporating altruism, reciprocity, and market incentives, and evaluates strategies to improve income distribution.

Findings

Shuffling gateway neighborhoods significantly improves income fairness.

Cost of free-riding altruism is non-negligible.

Simulation results show enhanced fairness with proposed methods.

Abstract

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. The challenge is to conceive incentives that are fair in regard to the income distribution among peers. Despite many systems using tokens to incentivize forwarding data, like Swarm, little is known about the interplay between incentives, storage-, and network-parameters. This paper aims to help fill this gap by developing Tit-for-Token (Tit4Tok), a framework to understand fairness. Tit4Tok realizes a triad of altruism (acts of kindness such as debt forgiveness), reciprocity (Tit-for-Tat's mirroring cooperation), and monetary rewards as desired in the free market. Tit4Tok sheds light on incentives across the accounting and settlement layers. We present a comprehensive exploration of different factors when incentivized peers share bandwidth in a libp2p-based network, including uneven distributions emerging when gateways provide data to users outside the network. We quantified the Income-Fairness with the Gini coefficient, using multiple model instantiations and diverse approaches for debt cancellation. We propose regular changes to the gateway neighborhood and show that our shuffling method improves the Income-Fairness from 0.66 to 0.16. We quantified the non-negligible cost of tolerating free-riding (altruism). The performance is evaluated by extensive computer simulations and using an IPFS workload to study the effects of caching.