The Application Of Genetic Algorithms And Neural Network Software Rejuvenation Technology

A common phenomenon which called "software aging" means the software systemdegrades with time. It always makes important influence to the system. In order tocounteract software aging, a proactive technique called "software rejuvenation" has beenproposed.Now there are two most popular software rejuvenation strategies, the time-basedstrategy and the measurement-based strategy. This paper discusses measurement-basedsoftware rejuvenation strategy, combined with Genetic Algorithms and neutral networkmethods to analyze the parameters of system performance which are monitored andcolleted periodically. In conclusion, it predicts resource consumption and the trend ofsoftware aging.This paper carried on the analysis to advantages and shortcoming of the BP neuralnetwork and the genetic algorithm, then this article combines the BP neural network andgenetic algorithms to full advantages of both which makes the new algorithms both havingthe BP neural network learning capability and robustness and the strong global searchcapability from the genetic algorithms. In the same time, some improvements have beenmade in this paper, such as the "growing up" process, the coding method, the parameterand the definition of the fitness function in the genetic algorithms. And during the trainingof the BP neural network, several learning methods have been compared.Comparing the result of the seventh day giving by the experiments and the test, thealgorithm in this paper has been proved to be doable. And then this paper forecast the datain the further. At last the experiment results given both by the genetic algorithm and by theneural network have been compared, and algorithm in this paper has been proved to beefficient.