Improved approximations for multiprocessor scheduling under uncertainty
Christopher Y. Crutchfield, Zoran Dzunic, Jeremy T. Fineman, David R. Karger, Jacob Scott · 2008
This paper presents improved approximation algorithms for the problem of multiprocessor scheduling under uncertainty (SUU), in which the execution of each job may fail probabilistically. This problem is motivated by the increasing use of distributed computing to handle large, computationally intensive tasks. In the SUU problem we are given n unit-length jobs and m machines, a directed acyclic graph G of precedence constraints among jobs, and unrelated failure probabilities qij for each job j when executed on machine i for a single timestep. Our goal is to find a schedule that minimizes the expected makespan.