In-network Distributed Analytics on Data-centric IoT Network for BI-service Applications

Authors(1) :-Dr. Nilamadhab Mishra

In-network distributed analytics are the major research challenges on data-centric IoT network. The rapid growing IoT applications on BI-services desire a generic framework in order to handle the dynamic analytic work load and disparate IoT data sources, because the generic framework can only perform the actions based on knowledge extracted from IoT data sources. So for knowledge analytics, there is always a need of novel framework and to achieve this, is a research task. The real time IoT driven applications always desire in-network analytics in order to transform the big business data into instant revenue of goldmines. The paper aims to discuss a knowledge analytic framework at IoT structure level and an IoT operational platform, so as to cop up with in-network IoT based BI- service applications. Here assume that each structure having a set of IoT nodes with one or more analytic nodes depending on application area of interest and the neediness of the deploying environment. Discussion shows the sound feasibility of Visual knowledge production frame in terms of knowledge abstraction, energy minimizations, and BI- service safety intensification.

Authors and Affiliations

Dr. Nilamadhab Mishra
Post Graduate Teaching & Research Dept., 09 School of Computing, Debre Berhan University, Debre Berhan 445, Ethiopia

Data-Centric IoT network, BI-service, IoT Application, In-Network Analytics

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 547-552
Manuscript Number : CSEIT172587
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Dr. Nilamadhab Mishra, "In-network Distributed Analytics on Data-centric IoT Network for BI-service Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.547-552 , September-October-2017.
Journal URL : http://ijsrcseit.com/CSEIT172587

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