Analyzing web server performance under dynamic user workloads

  • Authors:

  • RaúL PeñA-Ortiz;José A. Gil;Julio Sahuquillo;Ana Pont

  • Affiliations:

  • Universitat Politècnica de València, Departament d'Informítica de Sistemes i Computadors, Camí de Vera s/n, 46022 Valencia, Spain;Universitat Politècnica de València, Departament d'Informítica de Sistemes i Computadors, Camí de Vera s/n, 46022 Valencia, Spain;Universitat Politècnica de València, Departament d'Informítica de Sistemes i Computadors, Camí de Vera s/n, 46022 Valencia, Spain;Universitat Politècnica de València, Departament d'Informítica de Sistemes i Computadors, Camí de Vera s/n, 46022 Valencia, Spain

  • Venue:
  • Computer Communications
  • Year:
  • 2013

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Abstract

The increasing popularity of web applications has introduced a new paradigm where users are no longer passive web consumers but they become active contributors to the web, specially in the contexts of social networking, blogs, wikis or e-commerce. In this new paradigm, contents and services are even more dynamic, which consequently increases the level of dynamism in user's behavior. Moreover, this trend is expected to rise in the incoming web. This dynamism is a major adversity to define and model representative web workload, in fact, this characteristic is not fully represented in the most of the current web workload generators. This work proves that the web user's dynamic behavior is a crucial point that must be addressed in web performance studies in order to accurately estimate system performance indexes. In this paper, we analyze the effect of using a more realistic dynamic workload on the web performance metrics. To this end, we evaluate a typical e-commerce scenario and compare the results obtained using different levels of dynamic workload instead of traditional workloads. Experimental results show that, when a more dynamic and interactive workload is taken into account, performance indexes can widely differ and noticeably affect the stress borderline on the server. For instance, the processor usage can increase 30% due to dynamism, affecting negatively average response time perceived by users, which can also turn in unwanted effects in marketing and fidelity policies.