Scheduling Algorithms and Techniques with Variable Capacity Resources

This chapter surveys the impact of resource variability onto scheduling algorithms and metrics. First, we survey recent work related to energy-aware scheduling. Next, we discuss characteristics of current and future HPC and data centers, with a focus on power sources and their variation. Then, we investigate several scheduling techniques that can be deployed for batch schedulers to cope with, or even benefit from, changes in the number of computing resources. The chapter continues with a broad overview of the challenges that face scheduling techniques to account for variability, from new workload types up to combined optimization metrics. We conclude by sketching two case-studies, one for applications with variable running times, and one for risk-aware mapping jobs on dynamically changing platforms.