A strategic timing of arrivals to a linear slowdown processor sharing system

TL;DR

This paper analyzes strategic user behavior in a linear slowdown processor sharing system, deriving equilibrium solutions, highlighting computational challenges, and proposing an iterative algorithm to approximate equilibria.

Contribution

It introduces explicit equilibrium solutions for a two-user case, discusses the complexity of general solutions, and proposes an efficient iterative best-response algorithm.

Findings

Multiple equilibria can exist in the model.

Computational complexity grows exponentially with the number of users.

The proposed algorithm approximates equilibria effectively.

Abstract

We consider a discrete population of users with homogeneous service demand who need to decide when to arrive to a system in which the service rate deteriorates linearly with the number of users in the system. The users have heterogeneous desired departure times from the system, and their goal is to minimize a weighted sum of the travel time and square deviation from the desired departure times. Users join the system sequentially, according to the order of their desired departure times. We model this scenario as a non-cooperative game in which each user selects his actual arrival time. We present explicit equilibria solutions for a two-user example, namely the subgame perfect and Nash equilibria and show that multiple equilibria may exist. We further explain why a general solution for any number of users is computationally challenging. The difficulty lies in the fact that the objective functions are piecewise convex, i.e., non-smooth and non-convex. As a result, the minimization of the costs relies on checking all arrival and departure order permutations, which is exponentially large with respect to the population size. Instead we propose an iterated best-response algorithm which can be efficiently studied numerically. Finally, we compare the equilibrium arrival profiles to a socially optimal solution and discuss the implications.