2005/06/27 by Petra Berenbrink, Berenbrink, Petra, Tom Friedetzky +10
Computer Science · Engineering · Mathematics · #Computer Science and Game Theory (cs.GT) #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #FOS: Mathematics #Optimization and Control (math.OC) #Real-Time Systems Scheduling #Scheduling and Optimization Algorithms #cs.GT #math.OC
paper · pdf · doi:10.48550/arxiv.cs/0506098
openalex publication_date 2005/06/27 · arxiv created 2007/04/02 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Suppose that a set of m tasks are to be shared as equally as possible amongst a set of n resources. A game-theoretic mechanism to find a suitable allocation is to associate each task with a ``selfish agent'', and require each agent to select a resource, with the cost of a resource being the number of agents to select it. Agents would then be expected to migrate from overloaded to underloaded resources, until the allocation becomes balanced. Recent work has studied the question of how this can take place within a distributed setting in which agents migrate selfishly without any centralized control. In this paper we discuss a natural protocol for the agents which combines the following desirable features: It can be implemented in a strongly distributed setting, uses no central control, and has good convergence properties. For m≫ n, the system becomes approximately balanced (an ε-Nash equilibrium) in expected time O(loglog m). We show using a martingale technique that the process converges to a perfectly balanced allocation in expected time O(loglog m+n4). We also give a lower bound of Ω(max\loglog m,n\) for the convergence time.