Resource Allocation by Demand Based Optimization and Machine
P.Shyamala Bharathi1, M. Sujatha2, S.Shanthi3
1Dr. P. Shyamala Bharathi, Professor, Department of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India.
2Dr. M. Sujatha, Professor, Department of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India.
3Dr. S. Shanthi, Professor, Department of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India.
Manuscript received on September 18, 2019. | Revised Manuscript received on 27 September, 2019. | Manuscript published on October 10, 2019. | PP: 1388-1395 | Volume-8 Issue-12, October 2019. | Retrieval Number: L39341081219/2019©BEIESP | DOI: 10.35940/ijitee.L3934.1081219
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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: 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.
Keywords: Game Theory, OFDM, Resources Allocation, Scheduling, Energy Consumption
Scope of the Article: Cloud Resources Utilization in IoT