Match: A decentralized middleware for fair matchmaking in peer-to-peer markets

Abstract

Matchmaking is a core enabling element in peer-to-peer markets. To date, matchmaking is predominantly performed by proprietary algorithms, fully controlled by market operators. This raises fairness concerns as market operators effectively can hide, prioritize, or delay the orders of specific users. Blockchain technology has been proposed as an alternative for fair matchmaking without a trusted operator but is still vulnerable to specific fairness attacks. We present MATCH, a decentralized middleware for fair matchmaking in peer-to-peer markets. By decoupling the dissemination of potential matches from the negotiation of trade agreements, MATCH empowers end-users to make their own educated decisions and to engage in direct negotiations with trade partners. This approach makes MATCH highly resilient against malicious matchmakers that deviate from a specific matching policy. We implement MATCH and evaluate our middleware using real-world ride-hailing and asset trading workloads. It is demonstrated that MATCH maintains high matching quality, even when 75% of all matchmakers is malicious. We also show that the bandwidth usage and order fulfil latency of MATCH is orders of magnitude lower compared to matchmaking on an Ethereum blockchain.