Department of Computer Science | Institute of Theoretical Computer Science | CADMO
Theory of Combinatorial Algorithms
Prof. Emo Welzl and Prof. Bernd Gärtner
Department of Computer Science | Institute of Theoretical Computer Science | CADMO
Prof. Emo Welzl and Prof. Bernd Gärtner
| Mittagsseminar Talk Information |
Date and Time: Tuesday, November 25, 2025, 12:15 pm
Duration: 30 minutes
Location: OAT S15
Speaker: Sharat Ibrahimpur
We introduce a novel variant of stochastic load balancing that enables a quantitative trade-off between the practical benefits of non-adaptive policies and their performance limitations. Our model describes a solution in two stages. In the first stage, given only job-size distributions, we reserve a set of at most k machines for each job. In the second stage, after observing job-size realizations, we assign each job to one of its reserved machines. The goal is to minimize the expected makespan (i.e., the maximum load). If k is 1, we get the standard stochastic load balancing problem of finding a non-adaptive assignment with minimum expected makespan, and if k is equal to the number of machines, then we obtain an all-powerful omniscient optimum that can tailor the assignment arbitrarily to the job-size realizations. I will present a striking power-of-two-choices result for load balancing, showing that constant-factor approximations are achievable by reserving two machines per job relative to the omniscient and adaptive optimums. Joint work with David Aleman Espinosa, Naveen Garg, Neil Olver and Chaitanya Swamy.
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