期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2019
卷号：8
期号：1
页码：12-17
出版社：International Journal of Computer and Information Technology
摘要：Cloud computing infrastructure is becoming
indispensable in modern IT. Understanding the behavior nd
resource demands of cloud application workloads is key in data
center capacity planning, cloud infrastructure testing,
performance tuning and cloud computing research. Additionally,
cloud providers want to ensure Quality of Service (QoS), reduce
Service Level Agreement (SLA) violations and minimize energy
consumption in data centers. To achieve this, cloud workload
analysis is critical. However, scanty information is known about
the characteristics of these workloads because cloud providers are
not willing to share such information for confidentiality and
business reasons. Besides, there is lack of documented techniques
for workload characterization. In this paper, we perform the first
meticulous review on statistical techniques that can be used to
characterize cloud workloads. In this review, we identify a
statistical technique and its role in understanding cloud workload
characteristics. Throughout the review, we point out relevant
examples where and how such techniques have been applied.
Additionally, we have shown the sources cloud workloads and
their nature.
