Survey on prediction models of applications for resources provisioning in cloud

M Amiri, L Mohammad-Khanli - Journal of Network and Computer …, 2017 - Elsevier
According to the dynamic nature of cloud and the rapid growth of the resources demand in it,
the resource provisioning is one of the challenging problems in the cloud environment. The …

Are we done with business process compliance: state of the art and challenges ahead

M Hashmi, G Governatori, HP Lam… - Knowledge and Information …, 2018 - Springer
Literature on business process compliance (BPC) has predominantly focused on the
alignment of the regulatory rules with the design, verification and validation of business …

Predictive monitoring of business processes: a survey

AE Márquez-Chamorro, M Resinas… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Nowadays, process mining is becoming a growing area of interest in business process
management (BPM). Process mining consists in the extraction of information from the event …

Time and activity sequence prediction of business process instances

M Polato, A Sperduti, A Burattin, M Leoni - Computing, 2018 - Springer
The ability to know in advance the trend of running process instances, with respect to
different features, such as the expected completion time, would allow business managers to …

LSTM networks for data-aware remaining time prediction of business process instances

N Navarin, B Vincenzi, M Polato… - 2017 IEEE Symposium …, 2017 - ieeexplore.ieee.org
Predicting the completion time of business process instances would be a very helpful aid
when managing processes under service level agreement constraints. The ability to know in …

Biphase adaptive learning-based neural network model for cloud datacenter workload forecasting

J Kumar, D Saxena, AK Singh, A Mohan - Soft Computing, 2020 - Springer
Cloud computing promises elasticity, flexibility and cost-effectiveness to satisfy service level
agreement conditions. The cloud service providers should plan and provision the computing …

Prediction of remaining service execution time using stochastic petri nets with arbitrary firing delays

A Rogge-Solti, M Weske - … , ICSOC 2013, Berlin, Germany, December 2-5 …, 2013 - Springer
Companies realize their services by business processes to stay competitive in a dynamic
market environment. In particular, they track the current state of the process to detect …

Monitoring, prediction and prevention of sla violations in composite services

P Leitner, A Michlmayr, F Rosenberg… - … Conference on Web …, 2010 - ieeexplore.ieee.org
We propose the PREvent framework, which is a system that integrates event-based
monitoring, prediction of SLA violations using machine learning techniques, and automated …

A multi-view deep learning approach for predictive business process monitoring

V Pasquadibisceglie, A Appice… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The predictive business process monitoring is a family of online approaches to predict the
unfolding of running traces based on the knowledge learned from historical event logs. In …

Prediction of business process durations using non-Markovian stochastic Petri nets

A Rogge-Solti, M Weske - Information Systems, 2015 - Elsevier
Companies need to efficiently manage their business processes to deliver products and
services in time. Therefore, they monitor the progress of individual cases to be able to timely …