New approach to eliminate structural redundancy in case resource pools using α mutual information

Structural redundancy elimination in case resource pools （CRP） is critical for avoiding performance bottlenecks and maintaining robust decision capabilities in cloud computing services. For these purposes, this paper proposes a novel approach to ensure redundancy elimination of a reasoning system in CRP. By using α entropy and mutual information, functional measures to eliminate redundancy of a system are developed with respect to a set of outputs. These measures help to distinguish both the optimal feature and the relations among the nodes in reasoning networks from the redundant ones with the elimination criterion. Based on the optimal feature and its harmonic weight, a model for knowledge reasoning in CRP （CRPKR） is built to complete the task of query matching, and the missing values are estimated with Bayesian networks. Moreover, the robustness of decisions is verified through parameter analyses. This approach is validated by the simulation with benchmark data sets using cloud SQL. Compared with several state-of-the-art techniques, the results show that the proposed approach has a good performance and boosts the robustness of decisions.

Resource Reconstruction Algorithms for On-demand Allocation in Virtual Computing Resource Pool

Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.

On the Need to Integrate Traditional Chinese and Western Medicine, and Pool Research Resources

The Chinese Academy of Sci-ences (CAS) is implementing theknowledge innovation program(KIP) on a trial basis. In my opinion,our knowledge innovation targetsshould be first of all precise and,secondly, able to boost our work. Ispecialize in hematology and mo-lecular biology. Under the

Residual Resource Defragmentation Based on ECRC (Enhanced Cloud Resource Consolidating)

In cloud computing, server consolidation is the part where very few persons go through the same. By consolidating the unused server space, memory can be reused for another data allocation. The objective of this paper is to improve resource utilization. Residual resource fragmentation refers to the state of the data center where sufficient amount of residual resources are available for any new VM allocation. To achieve this, there are three methods followed here. Active physical servers are identified. Then the maximum utilization of the resources is found out. Finally the resources are allocated and scheduled using the developed algorithm. In this work, we have proposed a new algorithm enhanced cloud consolidating algorithm. This algorithm improves some of the qualities of the cloud consolidating algorithm. Here the allocation technique is based on the cost and the memory.

Pooling Resources

Boao forum participants discuss how the foreign currency reserve pool for Asian countries can promote regional financial

Fish trader’s gender and niches in a declining coral reef fishery:implications for sustainability

Introduction:The state of natural resources is greatly influenced by market access.Consequently,resource trader's incentives,decisions,and willingness to comply with manage-ment an influence efforts to achieve sustainabi lity.Trader's impacts will depend on their economic niches,which are influenced by cultural norms,skill,social relationshi ps,profitability,and the spatial scale of markets.Consequently,we examined the potential of traders to influence fisheries'sustainability by evaluating their jobs,gender roles,religion,socioeconomic status,association and perceptions of management systems,and future plans.We studied 142 traders in 19 Kenyan coral reef fisheries landing sites distributed among four gear management systems.Outcomes:We found a strong role of gender,geography,and religion in the participation of these fisheries that was primarily driven by fisheries'profitability.The associations suggest that overfished fisheries should retain traders with low education,capital,and savings-often women;whereas sustainable stocks favor the opposite characteristics,and often men.Conclusions:Therefore,managing for increasing yields,profits,and sustainability could exclude women traders unless they successfully access or adopt the more traditional male economic niche.Gender coexistence is most likely to be achieved by managing for inter-mediate resource levels where net production,catch,and fish body size diversity are high.Further,reducing risk and increasing the capital and mobility of women traders should reduce their chances of exclusion when fisheries are sustainable.