Performance Modeling of Multi-tiered Web Applications with Varying Service Demands

Kattepur, Ajay; Nambiar, Manoj

doi:10.15803/ijnc.6.1_64

Cited by 6 publications

(4 citation statements)

References 19 publications

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“…On the other hand QNs provide convenient primitives for constructing models, guarantee that are well-formed (i.e., stable, deadlock-free, etc), and can be solved efficiently. Work done by Kattepur and Nambiar [21] makes use of QNs to estimate performance of Web applications using algorithms such as Mean Value Analysis (MVA).…”

Section: Related Workmentioning

confidence: 99%

Timed protocol analysis of interconnected mobile IoT devices

Bouloukakis

Georgantas

Kattepur³

et al. 2021

J Internet Serv Appl

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With the emergence of the Internet of Things (IoT), application developers can rely on a variety of protocols and Application Programming Interfaces (APIs) to support data exchange between IoT devices. However, this may result in highly heterogeneous IoT interactions in terms of both functional and non-functional semantics. To map between heterogeneous functional semantics, middleware connectors can be utilized to interconnect IoT devices via bridging mechanisms. In this paper, we make use of the Data eXchange (DeX) connector model that enables interoperability among heterogeneous IoT devices. DeX interactions, including synchronous, asynchronous and streaming, rely on generic post and get primitives to represent IoT device behaviors with varying space/time coupling. Nevertheless, non-functional time semantics of IoT interactions such as data availability/validity, intermittent connectivity and application processing time, can severely affect response times and success rates of DeX interactions. We introduce timing parameters for time semantics to enhance the DeX API. The new DeX API enables the mapping of both functional and time semantics of DeX interactions. By precisely studying these timing parameters using timed automata models, we verify conditions for successful interactions with DeX connectors. Furthermore, we statistically analyze through simulations the effect of varying timing parameters to ensure higher probabilities of successful interactions. Simulation experiments are compared with experiments run on the DeX Mediators (DeXM) framework to evaluate the accuracy of the results. This work can provide application developers with precise design time information when setting these timing parameters in order to ensure accurate runtime behavior.

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Section: Related Workmentioning

confidence: 99%

Timed protocol analysis of interconnected mobile IoT devices

Bouloukakis

Georgantas

Kattepur³

et al. 2021

J Internet Serv Appl

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“…Instead, Wang et al [27] use Bayesian inference and Gibbs sampling to model service demand from queue length data. Kattepur and Nambiar [28] employ spline interpolation of service demands to propose a modified version of the multi-tiered web applications algorithm that provides more accurate estimates of maximum throughput and response time.…”

Section: Performance Estimation With Machine Learningmentioning

confidence: 99%

An efficient method for uncertainty propagation in robust software performance estimation

Aleti

Trubiani

Hoorn

et al. 2018

Journal of Systems and Software

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Software engineers often have to estimate the performance of a software system before having full knowledge of the system parameters, such as workload and operational profile. These uncertain parameters inevitably affect the accuracy of quality evaluations, and the ability to judge if the system can continue to fulfil performance requirements if parameter results are different from expected. Previous work has addressed this problem by modelling the potential values of uncertain parameters as probability distribution functions, and estimating the robustness of the system using Monte Carlo-based methods. These approaches require a large number of samples, which results in high computational cost and long waiting times.To address the computational inefficiency of existing approaches, we employ Polynomial Chaos Expansion (PCE) as a rigorous method for uncertainty propagation and further extend its use to robust performance estimation. The aim is to assess if the software system is robust, i.e., it can withstand possible changes in parameter values, and continue to meet performance requirements. PCE is a very efficient technique, and requires significantly less computations to accurately estimate the distribution of performance indices. Through three very different case studies from different phases of software development and heterogeneous application domains, we show that PCE can accurately (>97%) estimate the robustness of various performance indices, and saves up to 225 hours of performance evaluation time when compared to Monte Carlo Simulation.

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“…On the other hand QNs: provide convenient primitives for constructing models; guarantee that are well-formed (i.e., stable, deadlock-free, etc); and can be solved efficiently. Work done in [36] makes use of QNs to estimate performance of web applications using algorithms such as Mean Value Analysis (MVA).…”

Section: Related Workmentioning

confidence: 99%

Timeliness Evaluation of Intermittent Mobile Connectivity over Pub/Sub Systems

Bouloukakis

Georgantas

Kattepur

et al. 2017

Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

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Systems deployed in mobile environments are typically characterized by intermittent connectivity and asynchronous sending/reception of data. To create effective mobile systems for such environments, it is essential to guarantee acceptable levels of timeliness between sending and receiving mobile users. In order to provide QoS guarantees in different application scenarios and contexts, it is necessary to model the system performance by incorporating the intermittent connectivity. Queueing Network Models (QNMs) offer a simple modeling environment, which can be used to represent various application scenarios, and provide accurate analytical solutions for performance metrics, such as system response time. In this paper, we provide an analytical solution regarding the end-to-end response time between users sending and receiving data by modeling the intermittent connectivity of mobile users with QNMs. We utilize the publish/subscribe (pub/sub) middleware as the underlying communication infrastructure for mobile users. To represent the user's connections/disconnections, we model and solve analytically an ON/OFF queueing system by applying a mean value approach. Finally, we validate our model using simulations with real-world workload traces. The deviations between the performance results foreseen by the analytical model and the ones provided by the simulator are shown to be less than 5% for a variety of scenarios.

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Performance Modeling of Multi-tiered Web Applications with Varying Service Demands

Cited by 6 publications

References 19 publications

Timed protocol analysis of interconnected mobile IoT devices

Timed protocol analysis of interconnected mobile IoT devices

An efficient method for uncertainty propagation in robust software performance estimation

Timeliness Evaluation of Intermittent Mobile Connectivity over Pub/Sub Systems

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