TY - GEN

T1 - Equilibria of online scheduling algorithms

AU - Ashalgi, Itai

AU - Lucier, Brendan

AU - Tennenholtz, Moshe

PY - 2013

Y1 - 2013

N2 - We describe a model for competitive online scheduling algorithms. Two servers, each with a single observable queue, compete for customers. Upon arrival, each customer strategically chooses the queue with minimal expected wait time. Each scheduler wishes to maximize its number of customers, and can strategically select which scheduling algorithm, such as First-Come-First-Served (FCFS), to use for its queue. This induces a game played by the servers and the customers. We consider a non-Bayesian setting, where servers and customers play to maximize worst-case payoffs. We show that the re is a unique subgame perfect safety-level equilibrium and we describe the associated scheduling algorithm (which is not FCFS). The uniqueness result holds for both randomized and deterministic algorithms, with a different equilibrium algorithm in each case. When the goal of the servers is to minimize competitive ratio, we prove that it is an equilibrium for each server to apply FCFS: each server obtains the optimal competitive ratio of 2.

AB - We describe a model for competitive online scheduling algorithms. Two servers, each with a single observable queue, compete for customers. Upon arrival, each customer strategically chooses the queue with minimal expected wait time. Each scheduler wishes to maximize its number of customers, and can strategically select which scheduling algorithm, such as First-Come-First-Served (FCFS), to use for its queue. This induces a game played by the servers and the customers. We consider a non-Bayesian setting, where servers and customers play to maximize worst-case payoffs. We show that the re is a unique subgame perfect safety-level equilibrium and we describe the associated scheduling algorithm (which is not FCFS). The uniqueness result holds for both randomized and deterministic algorithms, with a different equilibrium algorithm in each case. When the goal of the servers is to minimize competitive ratio, we prove that it is an equilibrium for each server to apply FCFS: each server obtains the optimal competitive ratio of 2.

UR - http://www.scopus.com/inward/record.url?scp=84893371813&partnerID=8YFLogxK

M3 - منشور من مؤتمر

SN - 9781577356158

T3 - Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

SP - 67

EP - 73

BT - Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

T2 - 27th AAAI Conference on Artificial Intelligence, AAAI 2013

Y2 - 14 July 2013 through 18 July 2013

ER -