Resource Allocation via Message Passing

We propose a message-passing paradigm for resource allocation problems. This serves to connect ideas from the message passing literature, which has primarily grown out of the communications, statistical physics, and artificial intelligence communities, with a problem central to operations research. This also provides a new framework for decentralized management that generalizes price-based systems by allowing incentives to vary across activities and consumption levels. We demonstrate that message-based incentives, which are characterized by a new equilibrium concept, lead to system-optimal behavior for convex resource allocation problems, yet yield allocations superior to those from price-based incentives for non-convex problems. We describe a distributed and asynchronous message-passing algorithm for computing equilibrium messages and allocations, and demonstrate its merits in the context of a network resource allocation problem.