{"main_file_link":[{"url":"https://ieeexplore.ieee.org/document/9484599"}],"project":[{"name":"SFB 901 - Subproject C4","_id":"16"},{"name":"SFB 901 - Project Area C","_id":"4"},{"_id":"1","name":"SFB 901"}],"department":[{"_id":"75"}],"user_id":"63288","publisher":"IEEE Communications Society","citation":{"chicago":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE Communications Society, n.d. https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599.","ama":"Hasnain A, Karl H. Learning Coflow Admissions. In: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE Communications Society. doi:10.1109/INFOCOMWKSHPS51825.2021.9484599","bibtex":"@inproceedings{Hasnain_Karl, title={Learning Coflow Admissions}, DOI={10.1109/INFOCOMWKSHPS51825.2021.9484599}, booktitle={IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, publisher={IEEE Communications Society}, author={Hasnain, Asif and Karl, Holger} }","ieee":"A. Hasnain and H. Karl, “Learning Coflow Admissions,” in IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Vancouver BC Canada.","apa":"Hasnain, A., & Karl, H. (n.d.). Learning Coflow Admissions. In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). Vancouver BC Canada: IEEE Communications Society. https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599","short":"A. Hasnain, H. Karl, in: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, n.d.","mla":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, doi:10.1109/INFOCOMWKSHPS51825.2021.9484599."},"title":"Learning Coflow Admissions","related_material":{"link":[{"relation":"confirmation","url":"https://ieeexplore.ieee.org/document/9484599"}]},"date_updated":"2022-01-06T06:54:42Z","publication_status":"accepted","language":[{"iso":"eng"}],"ddc":["000"],"abstract":[{"lang":"eng","text":"Data-parallel applications are developed using different data programming models, e.g., MapReduce, partition/aggregate. These models represent diverse resource requirements of application in a datacenter network, which can be represented by the coflow abstraction. The conventional method of creating hand-crafted coflow heuristics for admission or scheduling for different workloads is practically infeasible. In this paper, we propose a deep reinforcement learning (DRL)-based coflow admission scheme -- LCS -- that can learn an admission policy for a higher-level performance objective, i.e., maximize successful coflow admissions, without manual feature engineering. LCS is trained on a production trace, which has online coflow arrivals. The evaluation results show that LCS is able to learn a reasonable admission policy that admits more coflows than state-of-the-art Varys heuristic while meeting their deadlines."}],"doi":"10.1109/INFOCOMWKSHPS51825.2021.9484599","keyword":["Coflow scheduling","Reinforcement learning","Deadlines"],"type":"conference","date_created":"2021-01-16T18:24:19Z","publication":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","status":"public","author":[{"first_name":"Asif","id":"63288","full_name":"Hasnain, Asif","last_name":"Hasnain"},{"id":"126","first_name":"Holger","full_name":"Karl, Holger","last_name":"Karl"}],"conference":{"end_date":"2021-05-13","name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","location":"Vancouver BC Canada","start_date":"2021-05-10"},"year":"2021","_id":"21005"}