Security Issues in Cloud based e-Learning Part 2(Architectural Aspects)

In this exploratory paper (2nd Part), we revealed Cloud computing Architecture, Public & Hybrid Cloud, PLE et

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

Perspectives of Integrated “Next Industrial Revolution” Clusters in Poland and Siberia

Rozdział z: Functioning of the Local Production Systems in Central and Eastern European Countries and Siberia. Case Studies and Comparative Studies, ed. Mariusz E. Sokołowicz.The paper presents the mapping of potential next industrial revolution clusters in Poland and Siberia. Deindustrialization of the cities and struggles with its consequences are one of the fundamental economic problems in current global economy. Some hope to find an answer to that problem is associated with the idea of next industrial revolution and reindustrialization initiatives. In the paper, projects aimed at developing next industrial revolution clusters are analyzed. The objective of the research was to examine new industrial revolution paradigm as a platform for establishing university-based trans-border industry clusters in Poland and Siberia47 and to raise awareness of next industry revolution initiatives.Monograph financed under a contract of execution of the international scientific project within 7th Framework Programme of the European Union, co-financed by Polish Ministry of Science and Higher Education (title: “Functioning of the Local Production Systems in the Conditions of Economic Crisis (Comparative Analysis and Benchmarking for the EU and Beyond”)). Monografia sfinansowana w oparciu o umowę o wykonanie projektu między narodowego w ramach 7. Programu Ramowego UE, współfinansowanego ze środków Ministerstwa Nauki i Szkolnictwa Wyższego (tytuł projektu: „Funkcjonowanie lokalnych systemów produkcyjnych w warunkach kryzysu gospodarczego (analiza porównawcza i benchmarking w wybranych krajach UE oraz krajach trzecich”))

Building the Infrastructure for Cloud Security: A Solutions View

For cloud users and providers alike, security is an everyday concern, yet there are very few books covering cloud security as a main subject. This book will help address this information gap from an Information Technology solution and usage-centric view of cloud infrastructure security. The book highlights the fundamental technology components necessary to build and enable trusted clouds. Here also is an explanation of the security and compliance challenges organizations face as they migrate mission-critical applications to the cloud, and how trusted clouds, that have their integrity rooted in hardware, can address these challenges. This book provides: Use cases and solution reference architectures to enable infrastructure integrity and the creation of trusted pools leveraging Intel Trusted Execution Technology (TXT). Trusted geo-location management in the cloud, enabling workload and data location compliance and boundary control usages in the cloud. OpenStack-based reference architecture of tenant-controlled virtual machine and workload protection in the cloud. A reference design to enable secure hybrid clouds for a cloud bursting use case, providing infrastructure visibility and control to organizations

Cloud Computing Adoption Model For Higher Education : A Comparison Study Between Malaysia And Jordan

Cloud computing is the solution for e-leering and social learning in Higher education.To provide these needs, this study identified the factors support for cloud computing adoption in Malaysian and Jordan Universities. In the cross-sectional study, respondents from297 out of 1329 for Universiti Teknikal Malaysia Melaka, Malaysia and 175 out of 323 for Al-Zaytoonah University, Jordan. The objective of this study is to check the main effect and tested the technology, organization and environmental (TOE) factors toward cloud computing adoption in universities. The results show significant support for major effects based on the theory of the TOE theory. The results also show the buffered impact of technology, organization and environmental on cloud computing adoption with institution influence as mediator between them and predicted the level of the adoption increase in universities. Useful recommendations and future research direction