Open AccessAn Economical Incorporation of IoT and Edge/ Cloud Computing for Dynamic Distribution of IoT Analytics and Organized Utilization of Network Resources
Author(s) -
M. Azhagiri,
Sanjesh Chevanan,
John Vivin,
Samuel Samuel,
Paul A. Davis
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a4921.119119
Subject(s) - cloud computing , enhanced data rates for gsm evolution , internet of things , analytics , computer science , edge device , edge computing , volume (thermodynamics) , core network , data science , data analysis , distributed computing , computer security , computer network , telecommunications , data mining , operating system , physics , quantum mechanics
As the Internet of Things (IoT) keeps on picking up application in telecommunication networks, an enormous number of devices are relied upon to be associated and utilised sooner rather than later. Wide scale Internet of Things (IoT) systems with several deployed IoT devices, such as sensors, actuators and so on, that generate a high volume of data is expected. This means that the volume of data is foretold to increase substantially. Customarily, cloud services have been executed in huge datacenters in the central network. Be that as it may, this is definitely not a long-haul adaptable choice as an exceptionally enormous number of gadgets are required to be associated and utilised sooner rather than later. An adaptable and productive arrangement is to disperse the IoT analytics between the core cloud and the network edge. This paper uses edge IoT analytics to viably and economically convey the information from the IoT between the core cloud and the network edge. First analytics can be completed on the edge cloud and just the essential information or results are sent for further investigation. We have identified an approach to make this operation increasingly affordable