Streaming Algorithms for Scheduling Jobs with Priorities

Authors

Bin Fu, The University of Texas Rio Grande ValleyFollow
Yumei Huo, CUNY
Hairong Zhao, Purdue University

Document Type

Conference Proceeding

Publication Date

7-18-2025

Abstract

We study the classical makespan minimization problem on parallel machines where jobs have bounded priority h. We develop the first one-pass streaming approximation scheme when all jobs’ processing times differ no more than a constant factor c and the number of jobs n is at least \tfrac{3 m h c}{2\epsilon } where m is the number of machines. The algorithm is then extended to the more general problem where the largest \alpha n jobs have no more than c factor difference for some constant \alpha, 0 < \alpha \le 1. For both problems, our algorithms can generate a “sketch schedule” for the applications where not only an approximate value, but also a schedule associated with the approximate value is needed. The algorithms can be applied and extended to the makespan minimization scheduling subject to precedence constraints where the precedence graph has bounded depth.

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Recommended Citation

Fu, Bin, Yumei Huo, and Hairong Zhao. "Streaming Algorithms for Scheduling Jobs with Priorities." In International Workshop on Combinatorial Algorithms, pp. 446-458. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-98740-3_32

Publication Title

Combinatorial Algorithms. IWOCA 2025. Lecture Notes in Computer Science

DOI

10.1007/978-3-031-98740-3_32