Data Science Workflows for the Cloud/Edge Computing Continuum

Author(s):  
Valerio Grossi ◽  
Roberto Trasarti ◽  
Patrizio Dazzi
Keyword(s):  
Author(s):  
Nilamadhab Mishra

The progressive data science and knowledge analytic tasks are gaining popularity across various intellectual applications. The main research challenge is to obtain insight from large-scale IoE data that can be used to produce cognitive actuations for the applications. The time to insight is very slow, quality of insight is poor, and cost of insight is high; on the other hand, the intellectual applications require low cost, high quality, and real-time frameworks and algorithms to massively transform their data into cognitive values. In this chapter, the author would like to discuss the overall data science and knowledge analytic contexts on IoE data that are generated from smart edge computing devices. In an IoE-driven e-BI application, the e-consumers are using the smart edge computing devices from which a huge volume of IoE data are generated, and this creates research challenges to traditional data science and knowledge analytic mechanisms. The consumer-end IoE data are considered the potential sources to massively turn into the e-business goldmines.


Author(s):  
George Tzanis ◽  
Ourania-Ioanna Fotopoulou

Undoubtedly the IoT is the future of technology, which can provide manifold benefits to health care. However, the posed challenges are also great. Concerning the analysis of healthcare data, various tools have been introduced to deal efficiently with the large volumes as well as the various peculiarities of data. The most popular representative of these modern tools is data mining. Although the KDD process has provided a lot of solutions, these techniques have to be scaled in order to deal with the new challenges posed by the big data paradigm. Cloud computing, as well as edge computing are the modern infrastructures that can provide the means to efficiently manage big data. Both cloud/edge computing and the IoT are very promising concepts of technology and their complementary characteristics assure that their integration, Cloud-IoT, provides a great potential of applications. The introduction of the Cloud-IoT paradigm in the healthcare domain can offer manifold benefits and opportunities that will considerably improve the quality of health care.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

2020 ◽  
Vol 140 (9) ◽  
pp. 1030-1039
Author(s):  
W.A. Shanaka P. Abeysiriwardhana ◽  
Janaka L. Wijekoon ◽  
Hiroaki Nishi

Author(s):  
Ping ZHAO ◽  
Jiawei TAO ◽  
Abdul RAUF ◽  
Fengde JIA ◽  
Longting XU

Author(s):  
Adyson Magalhaes Maia ◽  
Yacine Ghamri-Doudane ◽  
Dario Vieira ◽  
Miguel Franklin de Castro

Author(s):  
Shaveta Bhatia

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.


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