Accurate Modeling and Efficient QoS Analysis of Scalable Adaptive Systems under Bursty Workload
Financiación H2020 / H2020 Funds
Resumen: Fulfillment of QoS requirements for systems deployed in the Internet is becoming a must. A widespread characteristic of this kind of systems is that they are usually subject to highly variable and bursty workloads. The allocation of resources to fulfill QoS requirements during the peak workloads could entail a waste of computing resources. A solution is to provide the system with self-adaptive techniques that can allocate resources only when and where they are required. We pursue the QoS evaluation of workload-aware self-adaptive systems based on stochastic models. In particular, this work proposes an accurate modeling of the workload variability and burstiness phenomena based on previous approaches that use Markov Modulated Poisson Processes. We extend these approaches in order to accurately model the variations of the workload strongly influence the QoS of the self-adaptive system. Unfortunately, this stochastic modeling may lead to a non tractable QoS analysis. Consequently, this work also develops an efficient procedure for carrying out the QoS analysis.
Idioma: Inglés
DOI: 10.1016/j.jss.2017.05.022
Año: 2017
Publicado en: JOURNAL OF SYSTEMS AND SOFTWARE 130 (2017), 24-41
ISSN: 0164-1212

Factor impacto JCR: 2.278 (2017)
Categ. JCR: COMPUTER SCIENCE, THEORY & METHODS rank: 21 / 103 = 0.204 (2017) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, SOFTWARE ENGINEERING rank: 19 / 104 = 0.183 (2017) - Q1 - T1

Factor impacto SCIMAGO: 0.472 - Hardware and Architecture (Q1) - Software (Q2) - Information Systems (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T94
Financiación: info:eu-repo/grantAgreement/EC/H2020/644869/EU/Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements/DICE
Financiación: info:eu-repo/grantAgreement/ES/MICINN/TIN2014-58457-R
Tipo y forma: Article (PrePrint)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)

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