Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

Autor:	Cicotti, Giuseppe, Coppolino, Luigi, D'Antonio, Salvatore, Romano, Luigi
Rok vydání:	2014
Předmět:	Computer Science - Software Engineering
Druh dokumentu:	Working Paper
Popis:	As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study. Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitoring
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1405.0327 Zobrazit plný text záznamu View this record from Arxiv