A traditional classification approach based on keyword matching represents each text document as a set of keywords, without considering the semantic information, thereby, reducing the accuracy of classification. To solve this problem, a new classification approach based on Wikipedia matching was proposed, which represents each document as a concept vector in the Wikipedia semantic space so as to understand the text semantics, and has been demonstrated to improve the accuracy of classification. However, the immense Wikipedia semantic space greatly reduces the generation efficiency of a concept vector, resulting in a negative impact on the availability of the approach in an online environment. In this paper, we propose an efficient Wikipedia semantic matching approach to document classification. First, we define several heuristic selection rules to quickly pick out related concepts for a document from the Wikipedia semantic space, making it no longer necessary to match all the concepts in the semantic space, thus greatly improving the generation efficiency of the concept vector. Second, based on the semantic representation of each text document, we compute the similarity between documents so as to accurately classify the documents. Finally, evaluation experiments demonstrate the effectiveness of our approach, i.e., which can improve the classification efficiency of the Wikipedia matching under the precondition of not compromising the classification accuracy.
Generalized ring signcryption (GRSC) can realize ring signature and ring signcryption functions with only one key pair and one algorithm. It is very useful for a system with a large number of users, or whose function may be changed, or with limited storage space. We give a formal definition and security model of GRSC in the certificate-based cryptosystem setting and propose a concrete scheme by using bilinear pairings. The confidentiality of our scheme can be proved under the GBDH and CDH assumptions and the unforgeability of our scheme can be proved under [Formula: see text] and CDH assumptions in the random oracle model, and what is more, our scheme has unconditional anonymity. Compared with other certificateless ring signcryption schemes that use bilinear pairings, it is a highly efficient one.
Live migration of virtual machines (VMs) is useful for resource management of data centers and cloud platforms. The precopy algorithm is widely used for memory migration. However, when encountered with write-intensive workloads, the precopy's straightforward iteration strategy will become inefficient. Worse still, it is hard to tune the performance with the existing parameters, unless load characteristics are known in advance. In this paper, we propose an improved pre-filter-copy (PFC) algorithm. The main target is to reduce migration time and bandwidth resource consumption of the precopy algorithm, while keeping downtime at the same level. We designed a novel data filter to achieve this goal. In each round of iteration, it forecasts the pages that will be subsequently dirtied and then filters them from the send list. Meanwhile, previously filtered pages will be reconsidered, to see if they can be added to the send list. This ensures that the downtime will not be increased. Furthermore, a new parameter is proposed to improve the adaptivity of the precopy algorithm. Experimental results show that the PFC algorithm significantly reduces migration time and the amount of migrated data, while keeping the downtime at the same level.
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