58,176 research outputs found
Big Data Analytics for QoS Prediction Through Probabilistic Model Checking
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 monitorin
Challenges to describe QoS requirements for web services quality prediction to support web services interoperability in electronic commerce
Quality of service (QoS) is significant and necessary for web service applications quality assurance. Furthermore, web services quality has contributed to the successful implementation of Electronic Commerce (EC) applications. However, QoS is still the big issue for web services research and remains one of the main research questions that need to be explored. We believe that QoS should not only be measured but should also be predicted during the development and implementation stages. However, there are challenges and constraints to determine and choose QoS requirements for high quality web services. Therefore, this paper highlights the challenges for the QoS requirements prediction as they are not easy to identify. Moreover, there are many different perspectives and purposes of web services, and various prediction techniques to describe QoS requirements. Additionally, the paper introduces a metamodel as a concept of what makes a good web service
Survey on Additive Manufacturing, Cloud 3D Printing and Services
Cloud Manufacturing (CM) is the concept of using manufacturing resources in a
service oriented way over the Internet. Recent developments in Additive
Manufacturing (AM) are making it possible to utilise resources ad-hoc as
replacement for traditional manufacturing resources in case of spontaneous
problems in the established manufacturing processes. In order to be of use in
these scenarios the AM resources must adhere to a strict principle of
transparency and service composition in adherence to the Cloud Computing (CC)
paradigm. With this review we provide an overview over CM, AM and relevant
domains as well as present the historical development of scientific research in
these fields, starting from 2002. Part of this work is also a meta-review on
the domain to further detail its development and structure
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