@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}
}