A theoretical and empirical study of job scheduling in cloud computing environments: the weighted completion time minimization problem with capacitated parallel machines
Author:
Funder
Israel Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-023-05613-x.pdf
Reference37 articles.
1. Albagli-Kim, S., Shachnai, H., & Tamir, T. (2014). Scheduling jobs with dwindling resource requirements in clouds. In IEEE INFOCOM 2014-IEEE conference on computer communications (pp. 601–609). IEEE.
2. Balouka, N., & Cohen, I. (2021). A robust optimization approach for the multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, 291(2), 457–470.
3. Bianco, L., Blazewicz, J., Dell’Olmo, P., & Drozdowski, M. (1995). Scheduling multiprocessor tasks on a dynamic configuration of dedicated processors. Annals of Operations Research, 58(7), 493–517.
4. Bitton, S., Cohen, I., & Cohen, M. (2019). Joint repair sourcing and stocking policies for repairables using Erlang-A and Erlang-B queueing models. IISE Transactions, 51(10), 1151–1166.
5. Bougeret, M., Dutot, P.-F., Jansen, K., Robenek, C., & Trystram, D. (2011). Approximation algorithms for multiple strip packing and scheduling parallel jobs in platforms. Discrete Mathematics, Algorithms and Applications, 3(04), 553–586.
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