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Sharma, V.K. Soni, M.K. Mishra, and P. Bhuyan, \u201cA survey of job scheduling and resource management in grid computing,\u201d International Journal of Computer and Information Engineering, vol.4, no.4, pp.736-741, 2010."},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] M. Senthilkumar and P. Ilango, \u201cA survey on job scheduling in big data,\u201d Cybernetics and Information Technologies, vol.16, no.3, pp.35-51, 2016. 10.1515\/cait-2016-0033","DOI":"10.1515\/cait-2016-0033"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] B. Jamil, M. Shojafar, I. Ahmed, A. Ullah, K. Munir, and H. Ijaz, \u201cA job scheduling algorithm for delay and performance optimization in fog computing,\u201d Concurrency and Computation: Practice and Experience, vol.32, no.7, p.e5581, 2020. 10.1002\/cpe.5581","DOI":"10.1002\/cpe.5581"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] N.J.A. Harvey, R.E. Ladner, L. Lov\u00e1sz, and T. Tamir, \u201cSemi-matchings for bipartite graphs and load balancing,\u201d Journal of Algorithms, vol.59, no.1, pp.53-78, 2006. 10.1016\/j.jalgor.2005.01.003","DOI":"10.1016\/j.jalgor.2005.01.003"},{"key":"5","unstructured":"[5] N. Ailon, \u201cImproved bounds for online learning over the permutahedron and other ranking polytopes,\u201d Proc. Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS&apos;14), pp.29-37, PMLR, 2014."},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] D. Suehiro, K. Hatano, S. Kijima, E. Takimoto, and K. Nagano, \u201cOnline prediction under submodular constraints,\u201d Algorithmic Learning Theory: 23rd International Conference, ALT 2012, Lyon, France, Oct. 29-31, 2012. Proceedings 23, pp.260-274, Springer, 2012. 10.1007\/978-3-642-34106-9_22","DOI":"10.1007\/978-3-642-34106-9_22"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] S. Albers, \u201cBetter bounds for online scheduling,\u201d Proc. Twenty-Ninth Annual ACM Symposium on Theory of Computing, pp.130-139, 1997. 10.1145\/258533.258566","DOI":"10.1145\/258533.258566"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] S. Lattanzi, T. Lavastida, B. Moseley, and S. Vassilvitskii, \u201cOnline scheduling via learned weights,\u201d Proc. Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp.1859-1877, SIAM, 2020. 10.1137\/1.9781611975994.114","DOI":"10.1137\/1.9781611975994.114"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] Y. Bao, Y. Peng, C. Wu, and Z. Li, \u201cOnline job scheduling in distributed machine learning clusters,\u201d IEEE INFOCOM 2018-IEEE Conference on Computer Communications, pp.495-503, IEEE, 2018. 10.1109\/infocom.2018.8486422","DOI":"10.1109\/INFOCOM.2018.8486422"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] H. Tan, Z. Han, X.-Y. Li, and F.C.M. Lau, \u201cOnline job dispatching and scheduling in edge-clouds,\u201d IEEE INFOCOM 2017-IEEE Conference on Computer Communications, pp.1-9, IEEE, 2017. 10.1109\/infocom.2017.8057116","DOI":"10.1109\/INFOCOM.2017.8057116"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] J. Fakcharoenphol, B. Laekhanukit, and D. Nanongkai, \u201cFaster algorithms for semi-matching problems,\u201d ACM Transactions on Algorithms (TALG), vol.10, no.3, pp.1-23, 2014. 10.1145\/2601071","DOI":"10.1145\/2601071"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] C. Konrad and A. Ros\u00e9n, \u201cApproximating semi-matchings in streaming and in two-party communication,\u201d ACM Trans. Algorithms, vol.12, no.3, pp.1-21, April 2016. 10.1145\/2898960","DOI":"10.1145\/2898960"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Q. Zhao, Y. Zhu, H. Zhu, J. Cao, G. Xue, and B. Li, \u201cFair energy-efficient sensing task allocation in participatory sensing with smartphones,\u201d IEEE INFOCOM 2014-IEEE Conference on Computer Communications, pp.1366-1374, IEEE, 2014. 10.1109\/infocom.2014.6848070","DOI":"10.1109\/INFOCOM.2014.6848070"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] S. Gilbert, U. Meir, A. Paz, and G. Schwartzman, \u201cOn the complexity of load balancing in dynamic networks,\u201d Proc. 33rd ACM Symposium on Parallelism in Algorithms and Architectures, pp.254-264, 2021. 10.1145\/3409964.3461808","DOI":"10.1145\/3409964.3461808"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[15] N. Littlestone and M.K. Warmuth, \u201cThe weighted majority algorithm,\u201d Information and computation, vol.108, no.2, pp.212-261, 1994. 10.1006\/inco.1994.1009","DOI":"10.1006\/inco.1994.1009"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] B. Birnbaum and C. Mathieu, \u201cOn-line bipartite matching made simple,\u201d Acm Sigact News, vol.39, no.1, pp.80-87, 2008. 10.1145\/1360443.1360462","DOI":"10.1145\/1360443.1360462"},{"key":"17","unstructured":"[17] G. Goel and A. Mehta, \u201cOnline budgeted matching in random input models with applications to adwords,\u201d Proc. nineteenth annual ACM-SIAM symposium on Discrete algorithms, pp.982-991, 2008."},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] V.H. Manshadi, S.O. Gharan, and A. Saberi, \u201cOnline stochastic matching: Online actions based on offline statistics,\u201d Mathematics of Operations Research, vol.37, no.4, pp.559-573, 2012. 10.1287\/moor.1120.0551","DOI":"10.1287\/moor.1120.0551"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] B. Gamlath, M. Kapralov, A. Maggiori, O. Svensson, and D. 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Mirrokni, \u201cProportional allocation: Simple, distributed, and diverse matching with high entropy,\u201d Proc. 35th International Conference on Machine Learning, pp.99-108, PMLR, 2018."},{"key":"23","unstructured":"[23] X. Lu, Q. Wu, and W. Zhong, \u201cMulti-slots online matching with high entropy,\u201d Proc. 39th International Conference on Machine Learning, pp.14412-14428, PMLR, 2022."},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] S. Yasutake, K. Hatano, S. Kijima, E. Takimoto, and M. Takeda, \u201cOnline linear optimization over permutations,\u201d Algorithms and Computation: 22nd International Symposium, ISAAC 2011, Yokohama, Japan, Dec. 5-8, 2011. Proceedings 22, pp.534-543, Springer, 2011. 10.1007\/978-3-642-25591-5_55","DOI":"10.1007\/978-3-642-25591-5_55"},{"key":"25","unstructured":"[25] W.M. Koolen, M.K. Warmuth, J. 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