Abstract:Resource pooling improves system efficiency drastically in large stochastic systems, but its effective implementation in decentralized systems remains relatively underexplored. This paper studies how to incentivize resource pooling when agents are self-interested, and their states are private information. Our primary motivation is applications in the design of decentralized computing markets, among others. We study a standard multi-server queueing model in which each server is associated with an M/M/1 queue and aims to minimize its time-average job holding and processing costs. We design a simple token-based mechanism where servers can earn tokens by offering help and spend tokens to request help from other servers, all in their self-interest. The mechanism induces a complex game among servers. We employ the fluid mean-field equilibrium (FMFE) concept to analyze the system, combining mean-field approximation with fluid relaxation. This framework enables us to derive a closed-form characterization of servers' FMFE strategies. We show that these FMFE strategies approximate well the servers' rational behavior. We leverage this framework to optimize the design of the mechanism and present our main results: As the number of servers increases, the proposed mechanism incentivizes complete resource pooling---that is, the system dynamics and performance under our mechanism match those under centralized control. (Joint work with Yilun Chen and Chen Chen.)

Bio: Pengyu Qian is an Assistant Professor in the Operations & Technology Management department at the Questrom School of Business, Boston University. His research studies the design and analysis of marketplaces in dynamic settings, using tools from probability, optimization and game theory. He is interested in foundational models driven by challenges in sharing economy and the allocation of public resources. His research emphasizes algorithms/mechanisms that not only have good theoretical guarantees, but also are simple, robust, and hence practical for real-world systems. Pengyu is a recipient of the INFORMS JFIG Best Paper Prize. He earned his Ph.D. from Columbia Business School and his B.S. from Peking University.