Document Type
Article
Publication Date
10-30-2022
Abstract
In this paper, we design the first streaming algorithms for the problem of multitasking scheduling on parallel machines with shared processing. In one pass, our streaming approximation schemes can provide an approximate value of the optimal makespan. If the jobs can be read in two passes, the algorithm can find the schedule with the approximate value. This work not only provides an algorithmic big data solution for the studied problem, but also gives an insight into the design of streaming algorithms for other problems in the area of scheduling.
Recommended Citation
Fu, Bin, Yumei Huo, and Hairong Zhao. 2022. “Streaming Algorithms for Multitasking Scheduling with Shared Processing.” Discrete Applied Mathematics 320 (October): 346–55. https://doi.org/10.1016/j.dam.2022.06.019.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Title
Discrete Applied Mathematics
DOI
10.1016/j.dam.2022.06.019
Comments
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