Model-Driven Web Engineering Performance Prediction with Layered Queue Networks

Gambi, Alessio; Toffetti, Giovanni; Comai, Sara

doi:10.1007/978-3-642-16985-4_3

Cited by 3 publications

(7 citation statements)

References 13 publications

(17 reference statements)

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“…Measurement, Simulation modeling and Analytical modeling are the three approaches used in studying of a system's performance [11], [12], [13]. Measurement is a direct assessment of the actual or representative system under varying workloads, providing the most accurate results.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Performance modeling encapsulates the performance characteristics of a system that are available from its design in a performance model. In Simulation Modeling, a software representation of the system and its interactions are developed, and statistics collected from the model software's execution provide the performance metrics [13], [14]. Analytical modeling requires the use of mathematical equations for their solution.…”

Section: Performance Evaluationmentioning

confidence: 99%

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Performance measurement and analytic modeling of a web application

Shoaib¹

2021

Preprint

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The performance characteristics such as throughput, resource utilization and response time of a system can be determined through measurement, simulation modeling and analytic modeling. In this thesis, measurement and analytic modeling approaches are applied to study the performance of a Apache-PHP-PostgreSQL web application. Layered Queueing Network (LQN) analytic modeling has been used to represent the system's performance model. The measurements found from load testing are compared with model analysis results for model validation. This thesis aims to show that LQN performance models are versatile enough to allow development of highly granular and easily modifiable models of PHP-based web applications and furthermore are capable of performance prediction with sufficiently high accuracy. Lastly, the thesis also describes utilities and methods used for load testing and determination of service demand parameters in our research work which would aid in shortening time required in development and study of performance models of similar systems.

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Section: Performance Evaluationmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Performance measurement and analytic modeling of a web application

Shoaib¹

2021

Preprint

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“…Non-functional modelling: Finally, performance models from data obtained at runtime and LQNs can be combined with WebEng models to close the loop. This, as we proposed in [12], enables modelling taking into account non-functional concerns. For each modelling action, Web developers can receive an immediate feedback of the effects it will have in terms of system performances and costs.…”

Section: Model-driven F+nf Quality Frameworkmentioning

confidence: 99%

“…In this aspect, all non-functional concerns can be considered separately using software automation. Given a formal set of SLOs, solutions like the ones we proposed in [12] and [17] can be integrated and work in a totally autonomous fashion. In this way, novice users will only receive warnings in case the modelled pages / operations might violate SLOs, while more advanced users will be able to get complete predictions and monitoring of the response time, throughputs, and system configurations.…”

Section: Model-driven F+nf Quality Frameworkmentioning

confidence: 99%

“…The concept of Model-Driven Performance Engineering, for instance, was introduced by Frietzsche and Johannes in [11] and consists annotating models with performance information to enable performance analysis, for example with LQNs as in [15]. As we discuss more extensively in [12] our approach is similar, but in our case we can benefit from a continuous online estimation of LQN parameters and an arbitrarily accurate definition of the LQN starting from WebEng and PaaS models. Various authors have addressed the topic of migrating applications to the Cloud, focusing in particular on legacy applications as in [16].…”

Section: Related Workmentioning

confidence: 99%

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Web Engineering for Cloud Computing

Toffetti

2012

Current Trends in Web Engineering

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Abstract. Web Engineering has always been concerned with modelling the functional aspects of Web applications. Non-functional (e.g., performance, availability) properties of Web applications have traditionally been a minor concern in the Web engineering community and have been seen as technology-or system-related issues. The advent of Cloud computing, with substantial delegation of "system concerns" to infrastructure or platform providers, seems at a first sight to confirm the validity of this choice. But is this really true?We will argue that, in order to be able to actually profit from the Cloud computing paradigm, Web Engineering methodologies need several interventions transcending the platform-specific concerns of adapting to Cloud technologies.In this position paper, we call for a long-due revamp of Web engineering methodologies to become more sound engineering practices with respect to both functional and non-functional aspects of Web applications. To this end, we propose a methodological framework that preserves the advantages of model-driven development, but also takes into account performance and cost considerations for Cloud-based applications.

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Performance-Oriented VM Provisioning in Clouds

Shoaib¹

2021

Preprint

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Managing applications on the cloud requires extensive decision making on the part of the Application Provider (AP). When an application faces changing workload, the services of the application are either scaled up or down in response. The services run on Virtual Machines (VM) or container instances. APs decide on how the application scales through VM provisioning and the placement of the services on the VMs. Various drivers guide this decision making. Application performance and cost are two such drivers. This thesis answers the question of how APs can meet the performance constraints of their applications while minimizing the cost of the running VMs. Two versions of the problem are presented. The first version expects to meet mean response time constraints given a deployment configuration through the replication of VMs and addition of virtual processors. The presented solution is based on layered bottlenecks. A case study shows the solution meets response time constraints and uses fewer resources in comparison to a simple utilization based approach. The second version adds the minimization of cost as an objective, where VM-types having different cost rates are used. This problem does not require a deployment configuration and provides a complete solution, where resources can be added and removed. A novel solution based on the layered bottleneck strength value with genetic algorithm has been presented. For the case study, a decision maker is implemented for a web application. The proposed solution is compared with three algorithms, all of which run within the decision maker. The results from the case study show that the proposed solution provides shorter runtime than the exhaustive search, and is able to meet response time constraints with near optimal minimization of cost. The solution also results in better cost than a plain genetic algorithm and random search, at the expense of slightly longer runtime.

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Model-Driven Web Engineering Performance Prediction with Layered Queue Networks

Cited by 3 publications

References 13 publications

Performance measurement and analytic modeling of a web application

Performance measurement and analytic modeling of a web application

Web Engineering for Cloud Computing

Performance-Oriented VM Provisioning in Clouds

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