Workload Generators for Web-Based Systems: Characteristics, Current Status, and Challenges

Curiel, Mariela; Pont, Ana

doi:10.1109/comst.2018.2798641

Cited by 19 publications

(15 citation statements)

References 98 publications

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“…httperf [27], ProWGen [6]. A comprehensive survey of such workload generation tools can be found in [8]. While these publications and tools focus on interactive web-based applications, there are also publications focusing on data-intensive applications, e.g., MapReduce [11].…”

Section: Simulationmentioning

confidence: 99%

Multivariate Time Series Synthesis Using Generative Adversarial Networks

Leznik

Michalsky

Willis

et al. 2021

Proceedings of the ACM/SPEC International Conference on Performance Engineering

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Section: Simulationmentioning

confidence: 99%

Multivariate Time Series Synthesis Using Generative Adversarial Networks

Leznik

Michalsky

Willis

et al. 2021

Proceedings of the ACM/SPEC International Conference on Performance Engineering

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“…The performance of Web systems has a direct impact on the user experience. Thus, several workload models and workload generators have been proposed to characterize the workloads of different types of Web applications [3]. Barford and Crovella [12] introduced SURGE, a workload generator that employs the concept of user equivalents to generate traffic for Web servers.…”

Section: B Related Workmentioning

confidence: 99%

“…In the following subsection, we characterize each layer of our model by presenting the statistical distributions that best describe its variable. The final decision of what candidate distribution best fits a given variable is taken by comparing the Kolmogorov-Smirnov statistic 2 [23] and the Least Square Errors (LSE) 3 [24] of the fitted curves using a significance level of 0.05. To estimate the parameters of the distributions, we use the Maximum-Likelihood Estimation (MLE) method [25].…”

Section: ) Requested Tilesmentioning

confidence: 99%

“…The lack of publicly available datasets has notably contributed to this context. To illustrate this gap, a survey on workload generators for Web-based systems [3] reviewed more than 20 works on this topic in different types of applications (e.g., online social networks, video stream, and cloud computing services). None of them, however, focus on WMSs.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Characterization and Modeling of Web Map System Workload

et al. 2021

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Every month, billions of users access Web Map Systems (WMSs), such as Google Maps, to visualize geospatial data. A large number of users and the huge amount of data demanded by these applications make the design and development of WMSs a challenging task, especially in terms of performance and scalability. In this context, workload generators become crucial tools, as they help system administrators to plan the capacity of WMSs and design provisioning strategies for peak load scenarios. However, little is known about the workload patterns generated by WMS users. In this work, we use data anonymously collected from sessions of a client application of Google Maps to devise a model that describes how users of desktop terminals navigate in a Web map. Based on this model, we implement a workload generator called MUSeGen. We compare the workload patterns generated by MUSeGen against the workload patterns found in real data. Results show that MUSeGen generates synthetic traces whose navigation patterns closely match those found in real data. We also compare MUSeGen against HELP, a workload generator built upon previous findings on empirical knowledge on the usage of WMSs. Results show that the number of issued operations per session in HELP is, on average, four times lower than that in MUSeGen and the number of tiles requested is, on average, twice lower than that in our tool. In addition, navigation patterns in HELP are much simpler than in MUSeGen. These findings support the conclusion that MUSeGen produces more realistic workloads than HELP. To illustrate how such differences affect performance evaluation in practice, we carry out a performance evaluation of a real WMS under workloads generated by HELP and MUSeGen. Our evaluation shows that the system capacity under HELP is three times less than that obtained under MUSeGen, highlighting the value of MUSeGen.INDEX TERMS Web map user, tile-based systems, workload model, workload generation, performance evaluation.

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“…Simulation results are obtained from WCET benchmarks. Curiel and Pont (2018) describe new innovations in the WWW that involve dealing with more complex workload models. This survey summarizes and provides guidelines for these challenges.…”

Section: Related Workmentioning

confidence: 99%

Workload Characterization of Telecom Software

Ünlü

Boluk

2020

Konya Journal of Engineering Sciences

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Telecom software systems are a major aspect of telecommunications networks used for managing, administrating, auditing and monitoring purposes. One of the most significant features is the performance of the telecom software system, since there is a great variety of network elements in use within built systems through which the telecom software interacts. Workload characterization is an essential methodology for simulating load usage for a given infrastructure that is exposed to a production environment. Hence, exploring the characteristics of workloads well leads an increase on system efficiency and performance. Nevertheless, workload characterization has not been well examined yet for Telecom Software System. In this paper, a new workload characterization architecture is proposed and implemented to model the workload and simulate the behavior of the network element. This architecture provides information regarding the accuracy of the workload models for more precise performance testing. Additionally, we verify our workload characterization results obtained from our architecture in a real software system. Performance results show that proposed workload model-based simulation environment is promising to predict the performance of the software systems.

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Workload Generators for Web-Based Systems: Characteristics, Current Status, and Challenges

Cited by 19 publications

References 98 publications

Multivariate Time Series Synthesis Using Generative Adversarial Networks

Multivariate Time Series Synthesis Using Generative Adversarial Networks

Data-Driven Characterization and Modeling of Web Map System Workload

Workload Characterization of Telecom Software

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