TY - JOUR
T1 - Workload Characterization: A Survey Revisited
AU - Calzarossa, Maria Carla
AU - Calzarossa, Maria
AU - Massari, Luisa
AU - Tessera, Daniele
PY - 2016
Y1 - 2016
N2 - Workload characterization is a well-established discipline that plays a key role in many performance en-
gineering studies. The large-scale social behavior inherent in the applications and services being deployed
nowadays leads to rapid changes in workload intensity and characteristics and opens new challenging
management and performance issues. A deep understanding of user behavior and workload properties and
patterns is therefore compelling. This article presents a comprehensive survey of the state of the art of
workload characterization by addressing its exploitation in some popular application domains. In particular,
we focus on conventional web workloads as well as on the workloads associated with online social networks,
video services, mobile apps, and cloud computing infrastructures. We discuss the peculiarities of these work-
loads and present the methodological approaches and modeling techniques applied for their characterization.
The role of workload models in various scenarios (e.g., performance evaluation, capacity planning, content
distribution, resource provisioning) is also analyzed.
AB - Workload characterization is a well-established discipline that plays a key role in many performance en-
gineering studies. The large-scale social behavior inherent in the applications and services being deployed
nowadays leads to rapid changes in workload intensity and characteristics and opens new challenging
management and performance issues. A deep understanding of user behavior and workload properties and
patterns is therefore compelling. This article presents a comprehensive survey of the state of the art of
workload characterization by addressing its exploitation in some popular application domains. In particular,
we focus on conventional web workloads as well as on the workloads associated with online social networks,
video services, mobile apps, and cloud computing infrastructures. We discuss the peculiarities of these work-
loads and present the methodological approaches and modeling techniques applied for their characterization.
The role of workload models in various scenarios (e.g., performance evaluation, capacity planning, content
distribution, resource provisioning) is also analyzed.
KW - workload characterization
KW - workload measurements
KW - workload characterization
KW - workload measurements
UR - http://hdl.handle.net/10807/78664
U2 - 10.1145/2856127
DO - 10.1145/2856127
M3 - Article
SN - 0360-0300
VL - 2016
SP - 1
EP - 43
JO - ACM Computing Surveys
JF - ACM Computing Surveys
ER -