A General Mechanism Design Methodology for Social Utility Maximization with Linear Constraints
Abhinav Sinha, Achilleas Anastasopoulos

TL;DR
This paper introduces a unified, systematic mechanism design approach for social utility maximization with convex constraints, ensuring full Nash implementation, efficiency, individual rationality, and scalable message complexity.
Contribution
It presents a general methodology based on dual optimization to fully implement social utility maximization mechanisms with desirable properties across various applications.
Findings
Mechanisms achieve full Nash implementation of social utility maximization.
Message space size scales linearly with the number of agents.
Mechanisms ensure feasibility and strong budget balance both at and off equilibrium.
Abstract
Social utility maximization refers to the process of allocating resources in such a way that the sum of agents' utilities is maximized under the system constraints. Such allocation arises in several problems in the general area of communications, including unicast (and multicast multi-rate) service on the Internet, as well as in applications with (local) public goods, such as power allocation in wireless networks, spectrum allocation, etc. Mechanisms that implement such allocations in Nash equilibrium have also been studied but either they do not possess full implementation property, or are given in a case-by-case fashion, thus obscuring fundamental understanding of these problems. In this paper we propose a unified methodology for creating mechanisms that fully implement, in Nash equilibria, social utility maximizing functions arising in various contexts where the constraints are…
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