Maximizing the minimum load for selfish agents

We consider the problem of maximizing the minimum load for machines that are controlled by selfish agents, who are only interested in maximizing their own profit. Unlike the classical load balancing problem, this problem has not been considered for selfish agents until now. The goal is to design a truthful mechanism, i.e., one in which all users have an incentive to tell the truth about the speed of their machines. This then allows us to find good job assignments. It is known that this requires monotone approximation algorithms, in which the amount of work assigned to an agent does not increase if its bid (claimed cost per unit work) increases. For a constant number of machines, m, we show a monotone polynomial time approximation scheme (PTAS) with running time that is linear in the number of jobs. It uses a new technique for reducing the number of jobs while remaining close to the optimal solution. We use an FPTAS for the classical problem, i.e., where no selfish agents are involved,...

• Type: Journal
• Year: 2010
• Where: TCS
• Authors: Leah Epstein, Rob van Stee
• Keywords: Machines, Monotone Approximation, Selfish Agents, TCS 2010, Theoretical Computer Science