Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applications using token-based incentives. They are often disproportionally concentrated with small number of early adopters and high-resourced participants. Incentive mechanisms capable of addressing this problem are still poorly understood. This paper aims to help fill this gap by developing our Tit-for-Token (Tit4Tok) model. Tit4Tok realizes incentives based on the triad of altruism (selfless behavior), reciprocity (Tit-for-Tat), and monetary rewards compatible with a free market. Tit4Tok analyzes the effects of storage-, and network-parameters fine-tuning to achieve fair distribution of rewards for participants. 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.
Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Andrei Lebedev
, , , ,
Verónica del Carmen Estrada Galiñanes