An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks

Article Details
Title:	An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks
Article URLs:	https://doi.org/10.1109/RTSS.2018.00053 http://doi.ieeecomputersociety.org/10.1109/RTSS.2018.00053
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Authors:	Sandeep Kumar Bijinemula	Virginia Tech, Department of Electrical and Computer Engineering
	Aaron Willcock	Wayne State University, Department of Computer Science
	Thidapat Chantem	Virginia Tech, Department of Electrical and Computer Engineering
	Nathan Fisher	Wayne State University, Department of Computer Science
Sharing:	Research produced artifacts
Verification:	Authors have verified information
Artifact Evaluation Badge:	Artifacts for some papers are reviewed by an artifact evaluation, reproducibility, or similarly named committee. This is one such paper that passed review. awarded
Artifact URLs:	https://github.com/bsk1410/Efficient-Knapsack-for-AVR-tasks-RTSS2018
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NSF Award Numbers:	1618185, 1618979
DBLP Key:	conf/rtss/BijinemulaWCF18
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IEEE Real-Time Systems Symposium, RTSS 2018