The Community for Technology Leaders
2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity) (2015)
Chengdu, China
Dec. 19, 2015 to Dec. 21, 2015
ISBN: 978-1-5090-1892-5
pp: 662-667
ABSTRACT
This article proposes a path for doing Data Science using browsers as computing and data nodes. This novel idea is motivated by the cross-fertilized fields of desktop grid computing, data management in grids and clouds, Web technologies such as NoSQL tools, models of interactions and programming models in grids, cloud and Web technologies. We propose a methodology for the modeling, analyzing, implementation and simulation of a prototype able to run a MapReduce job in browsers. This work allows to better understand how to envision the big picture of Data Science in the context of the Javascript language for programming the middleware, the interactions between components and browsers as the operating system. We explain what types of applications may be impacted by this novel approach and, from a general point of view how a formal modeling of the interactions serves as a general guidelines for the implementation. Formal modeling in our methodology is a necessary condition but it is not sufficient. We also make round-trips between the modeling and the Javascript or used tools to enrich the interaction model that is the key point, or to put more details into the implementation. It is the first time to the best of our knowledge that Data Science is operating in the context of browsers that exchange codes and data for solving computational and data intensive programs. Computational and data intensive terms should be understand according to the context of applications that we think to be suitable for our system.
INDEX TERMS
Browsers, Prototypes, Computational modeling, Context, Adaptation models, Servers
CITATION

L. Abidi, C. Cerin, G. Fedak and H. He, "Towards an Environment for Doing Data Science That Runs in Browsers," 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)(SMARTCITY), Chengdu, China, 2016, pp. 662-667.
doi:10.1109/SmartCity.2015.145
292 ms
(Ver 3.3 (11022016))