Review on Fog Based Spectrum Sensing for Artificial Intelligence

Authors(2) :-A. Rethina Palin, I. Jeena Jacob

Wireless Mesh Network (MWN) could be divided into proactive routing, reactive routing and hybrid routing, which must satisfy the requirements related to scalability, reliability, flexibility, throughput, load balancing, congestion control and efficiency. DMN (Directional Mesh Network) become more adaptive to the local environments and robust to spectrum changes. The existing computing units in the mesh network systems are Fog nodes, the DMN architecture is more economic and efficient since it doesn’t require architecture- level changes from existing systems. The cluster head (CH) manages a group of nodes such that the network has the hierarchical structure for the channel access, routing and bandwidth allocation. The feature extraction and situational awareness is conducted, each Fog node sends the information regarding the current situation to the cluster head in the contextual format. A Markov logic network (MLN) based reasoning engine is utilized for the final routing table updating regarding the system uncertainty and complexity.

Authors and Affiliations

A. Rethina Palin
Francis Xavier Engineering College, Tirunelveli, TamilNadu, India
I. Jeena Jacob
Francis Xavier Engineering College, Tirunelveli, TamilNadu, India

WMN, Cloud Storage and Data Sharing.

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Publication Details

Published in : Volume 3 | Issue 8 | November-December 2018
Date of Publication : 2018-11-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 66-70
Manuscript Number : CSEIT183816
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

A. Rethina Palin, I. Jeena Jacob, "Review on Fog Based Spectrum Sensing for Artificial Intelligence", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 8, pp.66-70, November-December-2018. Available at doi : https://doi.org/10.32628/CSEIT183816
Journal URL : https://res.ijsrcseit.com/CSEIT183816 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

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