Volume : V, Issue : XII, December - 2016
Performance Optimization of Distributed Face Recognition Based on Genetic Algorithm
Jie Shi
Abstract :
Due to the tasks partition into the agents unevenly will cause the time of processing videos is too long and the CPU utilization of the agent which processes the most tasks will be explosion. In order to solve the above problems, an improved genetic algorithm was proposed to balance the tasks of agents. Firstly, each agent counted the number of the videos and the number of pedestrians in each video. Secondly, the agents send the statistical data to server by SOAP. Finally, server reallocated the videos to agents by using improved genetic algorithm. Experimental results show that the performance of distributed face recognition model has been effectively improved by using improved genetic algorithm to realize load balance. < clear="all" style="page-eak-before:auto;mso-eak-type:section-eak" />
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DOI : https://www.doi.org/10.36106/gjra
Cite This Article:
Jie Shi, Performance Optimization of Distributed Face Recognition Based on Genetic Algorithm, Global Journal For Research Analysis,Volume : 5 | Issue : 12 | December 2016
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Jie Shi, Performance Optimization of Distributed Face Recognition Based on Genetic Algorithm, Global Journal For Research Analysis,Volume : 5 | Issue : 12 | December 2016