
doi: 10.1145/2856127
handle: 10807/78664 , 11571/1109587
Workload characterization is a well-established discipline that plays a key role in many performance engineering 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 workloads 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.
mobile apps, workload characterization, cloud computing, user behavior, video services, workload measurements, Workload characterization, graph analysis, performance evaluation, 004, statistical techniques, online social networks, Web workload
mobile apps, workload characterization, cloud computing, user behavior, video services, workload measurements, Workload characterization, graph analysis, performance evaluation, 004, statistical techniques, online social networks, Web workload
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