Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
Algorithms for scheduling imprecise computations with timing constraints
SIAM Journal on Computing
Annals of Operations Research
Scheduling imprecise hard real-time jobs with cumulative error
Scheduling imprecise hard real-time jobs with cumulative error
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Approximation algorithms
Real-Time Systems
Algorithms for Scheduling Imprecise Computations with Timing Constraints to Minimize Maximum Error
IEEE Transactions on Computers
A Dynamic Priority Assignment Technique for Streams with (m, k)-Firm Deadlines
IEEE Transactions on Computers
Skip-Over: algorithms and complexity for overloaded systems that allow skips
RTSS '95 Proceedings of the 16th IEEE Real-Time Systems Symposium
Optimal Reward-Based Scheduling of Periodic Real-Time Tasks
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Enhanced fixed-priority scheduling with (m,k)-firm guarantee
RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
An O(n4) algorithm for preemptive scheduling of a single machine to minimize the number of late jobs
Operations Research Letters
Energy optimal schedules for jobs with multiple active intervals
Theoretical Computer Science
Energy reduction for scheduling a set of multiple feasible interval jobs
Journal of Systems Architecture: the EUROMICRO Journal
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Time-critical jobs in many real-time applications have multiple feasible intervals. Such a job is constrained to execute from start to completion in one of its feasible intervals. A job fails if the job remains incomplete at the end of the last feasible interval. Earlier works developed an optimal off-line algorithm to schedule all the jobs in a given job set and on-line heuristics to schedule the jobs in a best effort manner. This paper is concerned with how to find a schedule in which the number of jobs completed in one of their feasible intervals is maximized. We show that the maximization problem is $${\cal N}{\cal P}$$-hard for both non-preemptible and preemptible jobs. This paper develops two approximation algorithms for non-preemptible and preemptible jobs. When jobs are non-preemptible, Algorithm Least Earliest Completion Time First (LECF) is shown to have a 2-approximation factor; when jobs are preemptible, Algorithm Least Execution Time First (LEF) is proved being a 3-approximation algorithm. We show that our analysis for the two algorithms are tight. We also evaluate our algorithms by extensive simulations. Simulation results show that Algorithms LECF and LEF not only guarantee the approximation factors but also outperform other multiple feasible interval scheduling algorithms in average.