The Price of Anarchy: Centralized versus Distributed Resource Allocation Trade-offs

Abstract

Optimizing decision quality in large scale, distributed, resource allocation problems requires selecting the appropriate decision network architecture. Such resource allocation problems occur in distributed sensor networks, military air campaign planning, logistics networks, energy grids, etc. Optimal solutions require that demand, resource status, and allocation decisions are shared via messaging between geographically distributed, independent decision nodes. Jamming of wireless links, cyber attacks against the network, or infrastructure damage from natural disasters interfere with messaging and, thus, the quality of the allocation decisions. Our contribution described in the paper is a decentralized resource allocation architecture and algorithm that is robust to significant message loss and to uncertain demand arrival, and provides fine-grained, many-to-many combinatorial task allocation. Most importantly, it enables a conscious choice of the best level of decentralization under the expected degree of communications denial and quantifies the benefits of approximating status of peer nodes using proxy agents during temporary communications loss.