An Economical Incorporation of IoT and Edge/ Cloud Computing for Dynamic Distribution of IoT Analytics and Organized Utilization of Network Resources
M. Azhagiri1, Sanjesh Chevanan2, John Vivin3, Samuel4, Paul Davis5
1M. Azhagiri, Department of Computer Science and Engineering, SRM Institute of Science and Technology.
2Sanjesh Chevanan, Department of Computer Science and Engineering, SRM Institute of Science and Technology.
3John Vivin, Department of Computer Science and Engineering, SRM Institute of Science and Technology.
4Samuel, Department of Computer Science and Engineering, SRM Institute of Science and Technology.
5Paul Davis, Department of Computer Science and Engineering, SRM Institute of Science and Technology.
Manuscript received on October 16, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 2734-2736 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4921119119/2019©BEIESP | DOI: 10.35940/ijitee.A4921.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: IoT, Edge Computing, Datacenter, Cloud Network, Dynamic Distribution
Scope of the Article: IoT