Artificial Intelligence
Scheduling Periodic Jobs that Allow Imprecise Results
IEEE Transactions on Computers
Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
Operational rationality through compilation of anytime algorithms
Operational rationality through compilation of anytime algorithms
The Deferrable Server Algorithm for Enhanced Aperiodic Responsiveness in Hard Real-Time Environments
IEEE Transactions on Computers
Preemptive priority-based scheduling: an appropriate engineering approach
Advances in real-time systems
Optimal composition of real-time systems
Artificial Intelligence
Algorithms for Scheduling Real-Time Tasks with Input Error and End-to-End Deadlines
IEEE Transactions on Software Engineering
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
IEEE Transactions on Computers
Multiple Servers and Capacity Sharing for Implementing Flexible Scheduling
Real-Time Systems - Flexible Scheduling on Real-Time Systems
Real-Time Systems and Programming Languages: ADA 95, Real-Time Java, and Real-Time POSIX
Real-Time Systems and Programming Languages: ADA 95, Real-Time Java, and Real-Time POSIX
The Challenges of Real-Time AI
Computer
Priority Inheritance Protocols: An Approach to Real-Time Synchronization
IEEE Transactions on Computers
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
RTSS '95 Proceedings of the 16th IEEE Real-Time Systems Symposium
Combining (/sub m//sup n/)-hard deadlines and dual priority scheduling
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
Real-Time Systems
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Constructing deliberative real-time AI systems is challenging due to the high execution-time variance in AI algorithms and the requirement of worst-case bounds for hard real-time guarantees, often resulting in poor use of system resources. Using a motivating case study, the general problem of resource usage maximization is addressed. We approach the issues by employing a hybrid task model for anytime algorithms, which is supported by recent advances in fixed priority scheduling for imprecise computation. In particular, with a novel scheduling scheme based on Dual Priority Scheduling, hard tasks are guaranteed by schedulability analysis and scheduled in favor of optional and anytime components which are executed whenever possible for enhancing system utility. Simulation studies show satisfactory performance on the case study with the application of the scheduling scheme. We also suggest how aperiodic tasks can be scheduled effectively within the framework and how tasks can be prioritized based on their utilities by an efficient algorithm. These works form a comprehensive package of scheduling model, analysis, and algorithms based on fixed priority scheduling, providing a versatile platform where real-time AI applications can be suitably facilitated.