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 nonconvex problems. We describe a distributed and asynchronous message-passing algorithm for computing equilibrium messages and allocations, and we demonstrate its merits in the context of a network resource allocation problem.