Extraction of Cloud Storage Classification Rule Based on Genetic Algorithm
Shen Jia-ji · Jisuanji gongcheng · 2013
Aiming to data source's decentralized characteristic in cloud storage,taking consideration the problem of the relationship between extraction classify rule number and each agent and whole system's error rate,by using method of extracting the rule in distributed agents and merge rule set in center rule database under cloud storage situation,this paper proposes a guideline of the decreasing error rate of each agent and error rate upper limit of whole system with increasing extraction classify rule number under cloud storage distribution situation.Though formal proofing and theoretical derivation,the correctness of the proposed criterions is proved.The correctness of theoretical derivation is verified by the experiment,and experiment also shows that difficult between the return classification accuracy rate of distribution extract method and centralized extract method are approaching to a constant which proves the feasibility of the distribution extract method in this paper.