By Constandinos X. Mavromoustakis
This ebook reviews at the most up-to-date advances at the theories, practices, criteria and techniques which are regarding the trendy expertise paradigms, the cellular Cloud computing (MCC) and massive facts, because the pillars and their organization with the rising 5G cellular networks.
The booklet contains 15 conscientiously refereed chapters written via major foreign researchers, offering the readers with technical and medical information regarding a variety of features of massive info and cellular Cloud Computing, from simple suggestions to complicated findings, reporting the state of the art on tremendous facts administration. It demonstrates and discusses equipment and practices to enhance multi-source massive information manipulation innovations, in addition to the mixing of assets availability throughout the 3As (Anywhere, something, each time) paradigm, utilizing the 5G entry technologies.
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Extra resources for Advances in Mobile Cloud Computing and Big Data in the 5G Era
In Telecommunications from the University of East London in 2002. His research interests are in the ﬁelds of wireless networks, mobile communication systems, digital broadcasting technologies and interactive television systems, cognitive radio and dynamic access technologies, QoS/QoE techniques and network management techniques, as well as in radio-resource trading and optimisation techniques. He has participated in a number of national and European funded R&D projects, including the AC215 “CRABS”, IST-2000-26298 “MAMBO”, IST-2000-28521 “SOQUET”, IST-2001-34692 “REPOSIT”, IST-2002-FP6-507637 Big Data and Cloud Computing: A Survey … 41 “ENTHRONE”, “IMOSAN”, and as technical/scientiﬁc coordinator for the IST-2002-FP6-507312 “ATHENA” project.
In addition, the existing algorithms are not able to store data effectively because of the heterogeneity of big data. • Data transmission and curation: Since network bandwidth capacity is the major drawback in the cloud, data transmission is a challenge to overcome, especially when the volume of data is very large. For managing large-scale and structured datasets, data warehouses and data marts are good approaches. Data warehouses are relational database systems that enable the data storage, analysis and reporting, while the data marts are based on data warehouses and facilitate the analysis of them.
Sc. Sc. in Commerce and Marketing (with major in e-Commerce and Digital Marketing) from the Technological Educational Institute of Crete, Greece in 2012 (including a semester as an Erasmus exchange student at the Czech University of Life Sciences Prague, Czech Republic). , Greece. Mr. Georgios Skourletopoulos has publications at various international journals, conference proceedings, workshops and book chapters. His research interests lie in the general areas of mobile cloud computing, cloud computing, cloud-based software engineering, communications and networks.