Study on Differential Query Services Using Data Mining Techniques in Cloud Computing
Keywords:
Cloud Computing, Single Cloud, Multi-Cloud, Cloud StorageAbstract
Cloud processing as a developing innovation trend is estimated to reshape the advances in Information technology. In a cost-efficient cloud infrastructure, a client can tolerate a certain degree of interval while retrieving Information from the cloud to diminish costs. In this paper, we address two major issues in such an environment: secrecy and efficiency. We first review a hidden keyword based document recovery plan that was formerly proposed by Ostrovsky. Their structure licenses a client to get records of interest from a not trusted server without disclosing any info. The primary disadvantage is that it will cause a huge questioning above acquired on the cloud, and thus goes opposite the novel intention of cost efficiency. In this paper, we present a scheme, termed viable Information retrieval for positioned query, and based on a conglomeration and appropriation layer, to diminish questioning above acquired on the cloud. In viable Information retrieval for positioned query, inquiries are classified into numerous ranks, where a higher positioned query can get a higher proportion of coordinated files. A client can get records on demand by selecting inquiries of dissimilar ranks. Huge number of coordinated records is useful in this feature, but the client just wants a little subset of them. Under dissimilar parameter settings, broad estimations have been conducted together analytical models and on a genuine cloud infrastructure, in request to examine the usefulness of our schemes.
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