NDLI: Bounding and shaping the demand of generalized mixed-criticality sporadic task systems

Content Provider	Springer Nature Link
Author	Ekberg, Pontus Yi, Wang
Copyright Year	2013
Abstract	We generalize the commonly used mixed-criticality sporadic task model to let all task parameters (execution-time, deadline and period) change between criticality modes. In addition, new tasks may be added in higher criticality modes and the modes may be arranged using any directed acyclic graph, where the nodes represent the different criticality modes and the edges the possible mode switches. We formulate demand bound functions for mixed-criticality sporadic tasks and use these to determine EDF-schedulability. Tasks have different demand bound functions for each criticality mode. We show how to shift execution demand between different criticality modes by tuning the relative deadlines. This allows us to shape the demand characteristics of each task. We propose efficient algorithms for tuning all relative deadlines of a task set in order to shape the total demand to the available supply of the computing platform. Experiments indicate that this approach is successful in practice. This new approach has the added benefit of supporting hierarchical scheduling frameworks.
Starting Page	48
Ending Page	86
Page Count	39
File Format	PDF
ISSN	09226443
Journal	Real-Time Systems
Volume Number	50
Issue Number	1
e-ISSN	15731383
Language	English
Publisher	Springer US
Publisher Date	2013-06-15
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Real-time Mixed-criticality Demand bound functions Earliest deadline first Schedulability analysis Computer Systems Organization and Communication Networks Communications Engineering, Networks Special Purpose and Application-Based Systems Performance and Reliability Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Computer Networks and Communications Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications Modeling and Simulation

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