Online Job Scheduling with <i>K</i> Servers
Author:
Affiliation:
1. Computational Learning theory Team, RIKEN-Advanced Intelligence Project (AIP)
2. Department of Information Science and Technology, Kyushu University
3. Department of Informatics, Kyushu University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Link
https://www.jstage.jst.go.jp/article/transinf/E107.D/3/E107.D_2023FCP0005/_pdf
Reference25 articles.
1. [1] R. Sharma, V.K. Soni, M.K. Mishra, and P. Bhuyan, “A survey of job scheduling and resource management in grid computing,” International Journal of Computer and Information Engineering, vol.4, no.4, pp.736-741, 2010.
2. [2] M. Senthilkumar and P. Ilango, “A survey on job scheduling in big data,” Cybernetics and Information Technologies, vol.16, no.3, pp.35-51, 2016. 10.1515/cait-2016-0033
3. [3] B. Jamil, M. Shojafar, I. Ahmed, A. Ullah, K. Munir, and H. Ijaz, “A job scheduling algorithm for delay and performance optimization in fog computing,” Concurrency and Computation: Practice and Experience, vol.32, no.7, p.e5581, 2020. 10.1002/cpe.5581
4. [4] N.J.A. Harvey, R.E. Ladner, L. Lovász, and T. Tamir, “Semi-matchings for bipartite graphs and load balancing,” Journal of Algorithms, vol.59, no.1, pp.53-78, 2006. 10.1016/j.jalgor.2005.01.003
5. [5] N. Ailon, “Improved bounds for online learning over the permutahedron and other ranking polytopes,” Proc. Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS'14), pp.29-37, PMLR, 2014.
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