Statistical Analysis and Modeling of Heterogeneous Workloads on Amazon's Public Cloud Infrastructure
Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
Workload modeling in public cloud environments is challenging due to reasons such as infrastructure abstraction, workload heterogeneity and a lack of defined metrics for performance modeling. This paper presents an approach that applies statistical methods for distribution analysis, parameter estimation and Goodness-of-Fit (GoF) tests to develop theoretical (estimated) models of heterogeneous workloads on Amazon's public cloud infrastructure using compute, memory and IO resource utilization data.
Statistical Analysis and Modeling of Heterogeneous Workloads on Amazon's Public Cloud Infrastructure
Grand Wailea, Hawaii
Workload modeling in public cloud environments is challenging due to reasons such as infrastructure abstraction, workload heterogeneity and a lack of defined metrics for performance modeling. This paper presents an approach that applies statistical methods for distribution analysis, parameter estimation and Goodness-of-Fit (GoF) tests to develop theoretical (estimated) models of heterogeneous workloads on Amazon's public cloud infrastructure using compute, memory and IO resource utilization data.
https://aisel.aisnet.org/hicss-52/da/service_analytics/3