Relying on the knowledge of the pricing benefit of long-term reserved resource and multiplexing gains, cloud broker strives to minimize its cost by utilizing infrastructure resources from public cloud service provider...
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Today, many small and medium-sized companies want to share data for data mining;however, privacy and security concerns restrict such data sharing. Privacy-preserving data mining has emerged as a solution to this probl...
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Opponent modeling is an essential approach for building competitive computer agents in imperfect information games. This paper presents a novel approach to develop opp onent modeling techniques. The approach applies n...
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Servers and network contribute about 60% to the total cost of data center in cloud computing. How to efficiently place virtual machines so that the cost can be saved as much as possible, while guaranteeing the quality...
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ISBN:
(纸本)9781479975761
Servers and network contribute about 60% to the total cost of data center in cloud computing. How to efficiently place virtual machines so that the cost can be saved as much as possible, while guaranteeing the quality of service plays a critical role in enhancing the competitiveness of service cloud provider. Considering the heterogeneous servers and the random property of multiple resources requirements of virtual machines, the problem is formulated as a multi-objective nonlinear programming in this paper. Virtual machine cluster with higher traffic is made staying together. This reduces the communication delay while saving the inter-server bandwidth consumption, especially the relatively scarce higher level bandwidth, by exploiting the topology information of data center. At the same time, statistic multiplex and newly defined “similarity” techniques are leveraged to consolidate virtual machines. The violation of resource capacity is kept at any designated minimal probability. Thus the quality of service will not be deteriorated while saving servers and network cost. An offline and an online algorithms are proposed to address this problem. Experiments compared with several baseline algorithms show the validity of the new algorithms: more cost is cut down at less computation effort.
Nowadays wireless sensor network (WSN) is widely used in human-centric applications and environmental monitoring. Different institutes deploy their own WSNs for data collection and processing. It becomes a challenging...
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Nowadays wireless sensor network (WSN) is widely used in human-centric applications and environmental monitoring. Different institutes deploy their own WSNs for data collection and processing. It becomes a challenging problem when institutes collaborate to do data mining while intend to keep data privacy on each side. Privacy preserving data mining (PPDM) is used to solve the above problem, which enables multiple parties owning confidential data to run a data mining algorithm on their combined data, without revealing any unnecessary information to each other. However, due to the huge amount of data collected and the complexity of data mining algorithms, it is preferable to outsource most of the computations to the cloud. In this paper, we consider a scenario in which two parties with weak computational power need jointly run a k-means clustering protocol, at the same time outsource most of the computation of the protocol to the cloud. As a result, each party can have the correct result calculated by the data from both parties with most of the computation outsourced to the cloud. As for privacy, the data owned by one party should be kept confidential from both the other party and the cloud.
Predicate encryption allows flexible fine-grained control over access to encrypted data and achieves attribute *** [1] supporting inner product is the most expressive predicate encryption scheme currently with large a...
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Predicate encryption allows flexible fine-grained control over access to encrypted data and achieves attribute *** [1] supporting inner product is the most expressive predicate encryption scheme currently with large amount of pre-process and huge expenses of *** our scheme,we propose a new predicate encryption which prepares the ciphertext C for each attribute values one by one,and later transforms to the ciphertexts C’ corresponding to different *** can greatly reduce the pre-processing time and the storage from O(2n ) to O(n ) compared to KSW [1],where n is the total number of attribute values in one record of a table (In the enterprise development database,n is dozens or even hundreds).The security of our scheme is against chosen-plaintext attacks in the standard model.
Risk dominance strategy is a complementary part of game theory decision strategy besides payoff dominance. It is widely used in decision of economic behavior and other game conditions with risk characters. In research...
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