Affiliation:
1. Washington University in Saint Louis
2. Sapienza University of Rome
Abstract
The Conditional DAG (CDAG) task model is used for modeling multiprocessor real-time systems containing conditional expressions for which outcomes are not known prior to their evaluation. Feasibility analysis for CDAG tasks upon multiprocessor platforms is shown to be complete for the complexity class
pspace
; assuming
np
≠
pspace
, this result rules out the use of Integer Linear Programming solvers for solving this problem efficiently. It is further shown that there can be no pseudo-polynomial time algorithm that solves this problem unless
p
=
pspace
.
Publisher
Association for Computing Machinery (ACM)
Subject
Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Modeling and Simulation,Software
Reference18 articles.
1. Sanjoy Baruah. 2020. Feasibility analysis of conditional DAG tasks is co- \(\mathrm{NP^{\mbox{NP}} }\) -hard (why this matters). In Proceedings of the 29th International Conference on Real-Time and Network Systems (RTNS’21). ACM, 165–172.
2. Sanjoy Baruah, Vincenzo Bonifaci, and Alberto Marchetti-Spaccamela. 2015. The global EDF scheduling of systems of conditional sporadic DAG tasks. In Proceedings of the 26th Euromicro Conference on Real-Time Systems (ECRTS’15). IEEE Computer Society Press, 222–231.
3. Sanjoy Baruah, Vincenzo Bonifaci, Alberto Marchetti-Spaccamela, Leem Stougie, and Andreas Wiese. 2012. A generalized parallel task model for recurrent real-time processes. In Proceedings of the IEEE Real-Time Systems Symposium (RTSS’12). IEEE Computer Society Press, 63–72.