Scheduling for Heavy-Tailed and Light-Tailed Workloads in Queueing Systems

• Main Author: Nair, Jayakrishnan U.
• Format: Others
• Published: 2012
• Online Access: https://thesis.library.caltech.edu/7121/1/thesis.pdf; Nair, Jayakrishnan U. (2012) Scheduling for Heavy-Tailed and Light-Tailed Workloads in Queueing Systems. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/AAXJ-EX10. https://resolver.caltech.edu/CaltechTHESIS:06012012-134536732 <https://resolver.caltech.edu/CaltechTHESIS:06012012-134536732>

<p>In much of classical queueing theory, workloads are assumed to be light-tailed, with job sizes being described using exponential or phase type distributions. However, over the past two decades, studies have shown that several real-world workloads exhibit heavy-tailed characteristics. As a result, there has been a strong interest in studying queues with heavy-tailed workloads. So at this stage, there is a large body of literature on queues with light-tailed workloads, and a large body of literature on queues with heavy-tailed workloads. However, heavy-tailed workloads and light-tailed workloads differ considerably in their behavior, and these two types of workloads are rarely studied jointly.</p> <p>In this thesis, we design scheduling policies for queueing systems, considering both heavy-tailed as well as light-tailed workloads. The motivation for this line of work is twofold. First, since real world workloads can be heavy-tailed or light-tailed, it is desirable to design schedulers that are robust in their performance to distributional assumptions on the workload. Second, there might be scenarios where a heavy-tailed and a light-tailed workload interact in a queueing system. In such cases, it is desirable to design schedulers that guarantee fairness in resource allocation for both workload types.</p> <p>In this thesis, we study three models involving the design of scheduling disciplines for both heavy-tailed as well as light-tailed workloads. In Chapters 3 and 4, we design schedulers that guarantee robust performance across heavy-tailed and light-tailed workloads. In Chapter 5, we consider a setting in which a heavy-tailed and a light-tailed workload complete for service. In this setting, we design scheduling policies that guarantee good response time tail performance for both workloads, while also maintaining throughput optimality.</p>