Open AccessResource Allocation by Demand Based Optimization and Machine
Author(s) -
P. Shyamala Bharathi*,
M. Sujatha,
S. Shanthi
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.l3934.1081219
Subject(s) - computer science , resource allocation , quality of service , scheduling (production processes) , channel (broadcasting) , optimization problem , channel allocation schemes , real time computing , mathematical optimization , distributed computing , computer network , wireless , telecommunications , algorithm , mathematics
In real-time multimedia usage the resource allocation for the modern communication is very much needed in-order to overcome certain problems or degradation happening in the communication channels. The quality of the communication is reduced due to the TVWS (Television White Space), variable BER signal requires variable channel allocation procedures and Qos depends on the various applications. These problems in the OFDM should be corrected continuously by keeping track of channel situation so that to provide a long term video streaming in good QoS. The energy distribution for the video is high the application requirement is higher also the occurrence of multiple BER will leads to the challenging environment to control. The main objective of this paper is to enhance a Game theory based algorithm incorporated with demand optimization algorithm and scheduling algorithm for machine learning to take decision in nonlinear space, which results in a system with good channel awareness and an adaptive resource allocation process. The effect of interference due to this procedure is checked and accordingly allocations are done