Workload Characterization

Abstract

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.

Multi-formalism Models for Performance Engineering

“…With respect to the study of computing infrastructures workload in general (including the identification of patterns), Calzarossa et al [10] presented an interesting survey on the subject. Workload remains a key indicator to correctly match the Quality of Service (QoS) and Quality of Experience (QoE) and to adequately respond to energy saving policies and resource provisioning requests.…”

“…However, such tasks imply a risk, since collecting big volumes of data can add a significant workload to the system, which can be mitigated by choosing appropriate sampling techniques, assuming that the sample is correctly selected (this and other issues are discussed in [11]. The work in [10] reviews the main techniques used to analyze the system performance, ranging from statistical analysis to the usage of graphs and stochastic processes.…”

User Behavior in Mass Media Websites

“…A deeper essay comparing techniques for both client and server side analysis is found in (Calzarossa et al, 2016).…”

“…In (Calzarossa et al, 2016) and (Singal et al, 2014) there is an extensive analysis of evidences, methodologies, techniques as well as the state of the art in video analysis, social networks analysis, etc. Most of these works are based on Google Analytics and they are applied on the web.…”

Ferramentas de avaliação de desempenho para servidores web: análise, implementação de melhorias e testes

“…Ainda que alguns sistemas exijam um método específico para a caracterização de sua carga, há uma metodologia (Menascé k Almeida, 1998) que pode ser utilizada, de maneira geral, 11a caracterização de qualquer tipo de carga (Calzarossa & Serazzi, 1993;Vallamsetty, 2003). • Identificar os intervalos de tempo (time windows), que definem as sessões de medida.…”