Server Cloud Scheduling

M. Maack, F. Meyer auf der Heide, S. Pukrop, Algorithmica (2023).

No fulltext has been uploaded.
Journal Article | Published | English
<jats:title>Abstract</jats:title><jats:p>Consider a set of jobs connected to a directed acyclic task graph with a fixed source and sink. The edges of this graph model precedence constraints and the jobs have to be scheduled with respect to those. We introduce the server cloud scheduling problem, in which the jobs have to be processed either on a single local machine or on one of infinitely many cloud machines. For each job, processing times both on the server and in the cloud are given. Furthermore, for each edge in the task graph, a communication delay is included in the input and has to be taken into account if one of the two jobs is scheduled on the server and the other in the cloud. The server processes jobs sequentially, whereas the cloud can serve as many as needed in parallel, but induces costs. We consider both makespan and cost minimization. The main results are an FPTAS for the makespan objective for graphs with a constant source and sink dividing cut and strong hardness for the case with unit processing times and delays.</jats:p>
Publishing Year
Journal Title

Cite this

Maack M, Meyer auf der Heide F, Pukrop S. Server Cloud Scheduling. Algorithmica. Published online 2023. doi:10.1007/s00453-023-01189-x
Maack, M., Meyer auf der Heide, F., & Pukrop, S. (2023). Server Cloud Scheduling. Algorithmica.
@article{Maack_Meyer auf der Heide_Pukrop_2023, title={Server Cloud Scheduling}, DOI={10.1007/s00453-023-01189-x}, journal={Algorithmica}, publisher={Springer Science and Business Media LLC}, author={Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon}, year={2023} }
Maack, Marten, Friedhelm Meyer auf der Heide, and Simon Pukrop. “Server Cloud Scheduling.” Algorithmica, 2023.
M. Maack, F. Meyer auf der Heide, and S. Pukrop, “Server Cloud Scheduling,” Algorithmica, 2023, doi: 10.1007/s00453-023-01189-x.
Maack, Marten, et al. “Server Cloud Scheduling.” Algorithmica, Springer Science and Business Media LLC, 2023, doi:10.1007/s00453-023-01189-x.


Marked Publications

Open Data LibreCat

Search this title in

Google Scholar