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AUSAI
2005
Springer

Adaptive Utility-Based Scheduling in Resource-Constrained Systems

13 years 9 months ago
Adaptive Utility-Based Scheduling in Resource-Constrained Systems
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework for making repeated scheduling decisions based on dynamically observed information about unscheduled jobs and system’s resources. This framework generalizes the standard scheduling problem to a resource-constrained environment, where resource allocation (RA) decisions (how many CPUs to allocate to each job) have to be made concurrently with the scheduling decisions (when to execute each job). Discrete-time Optimal Control theory is used to formulate the optimization problem of finding the scheduling/RA policy that maximizes the average utility per time step obtained from completed jobs. We propose a Reinforcement Learning (RL) architecture for solving the NP-hard Optimal Control problem in real time, and our experimental results demonstrate the feasibility and benefits of the proposed approach. Content Area...
David Vengerov
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where AUSAI
Authors David Vengerov
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