Cloud Computing. Concepts, Technology & Architecture

TL;DR: Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behavior as mentioned in this paper, which poses hard challenges in terms of information fusion, data volumes, data speed, and network/energy efficiency, to mention but the most pressing ones.

TL;DR: Simulation results show that compared with the existing works, the proposed approach has reduced the failure number of task deployment events obviously, improved the throughput, and optimized the external services performance of cloud data centers.

TL;DR: This article defines and discusses some of the major challenges in the healthcare systems which can be effectively tackled by the recent advancement in ICT technologies and describes the architectural components of the proposed framework, SmartHealth, for big data analytics services and its various applications in the Healthcare domain.

TL;DR: It is found that successfully adopting FAAS requires a different mental model, where systems are primarily constructed by composing pre-existing services, with FaaS often acting as the “glue” that brings these services to the application developers, and tooling availability and maturity remains a major difficulty.

TL;DR: Simulation results show that compared with the existing works, the proposed approach has reduced the failure number of task deployment events obviously, improved the throughput, and optimized the external services performance of cloud data centers.

TL;DR: A new metamodel-based approach for integrating Internet of Things architectural objects is described, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.

TL;DR: In this article, the authors investigated both detecting and categorizing anomalies rather than just detecting, which is a common trend in the contemporary research works, and argued that such categorization can be applied to multi-cloud environments using the same machine learning techniques.

TL;DR: This short paper derives metrics for scalability, elasticity, and efficiency properties of cloud computing systems using the goal question metric (GQM) method and shows that the GQM plan allows to classify existing metrics.