@InProceedings{peng_et_al:LIPIcs.ECRTS.2019.20, author = {Peng, Bo and Fisher, Nathan and Chantem, Thidapat}, title = {{Fast and Effective Multiframe-Task Parameter Assignment Via Concave Approximations of Demand}}, booktitle = {31st Euromicro Conference on Real-Time Systems (ECRTS 2019)}, pages = {20:1--20:22}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-110-8}, ISSN = {1868-8969}, year = {2019}, volume = {133}, editor = {Quinton, Sophie}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2019.20}, URN = {urn:nbn:de:0030-drops-107578}, doi = {10.4230/LIPIcs.ECRTS.2019.20}, annote = {Keywords: generalized multiframe task model (GMF), generalized multiframe task model with parameter adaptation (GMF-PA), self-suspending tasks, uniprocessor scheduling, mixed-integer linear programming, concave approximation, linear programming} }
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