Autonomic resource management in virtualized data centers using fuzzy logic-based approaches

Data centers, as resource providers, are expected to deliver on performance guarantees while optimizing resource utilization to reduce cost. Virtualization techniques provide the opportunity of consolidating multiple separately managed containers of virtual resources on underutilized physical servers. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared physical resources to virtual containers and the management of their capacities to meet service-quality targets at the least cost. This paper proposes a two-level resource management system to dynamically allocate resources to individual virtual containers. It uses local controllers at the virtual-container level and a global controller at the resource-pool level. An important advantage of this two-level control architecture is that it allows independent controller designs for separately optimizing the performance of applications and the use of resources. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the local controller designs is their use of fuzzy logic-based approaches to efficiently and robustly deal with the complexity and uncertainties of dynamically changing workloads and resource usage. The global controller determines the resource allocation based on a proposed profit model, with the goal of maximizing the total profit of the data center. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.

widgetcon: A website and program for quick conversion among common population genetic data formats

One of the most tedious steps in genetic data analyses is the reformatting data generated with one program for use with other applications. This conversion is necessary because comprehensive evaluation of the data may be based on different algorithms included in diverse software, each requiring a distinct input format. A platform‐independent and freely available program or a web‐based tool dedicated to such reformatting can save time and efforts in data processing. Here, we report widgetcon , a website and a program which has been developed to quickly and easily convert among various molecular data formats commonly used in phylogenetic analysis, population genetics, and other fields. The web‐based service is available at https://www.widgetcon.net . The program and the website convert the major data formats in four basic steps in less than a minute. The resource will be a useful tool for the research community and can be updated to include more formats and features in the future.     

A Spatial Dirichlet Process Mixture Model for Clustering Population Genetics Data

Summary Identifying homogeneous groups of individuals is an important problem in population genetics. Recently, several methods have been proposed that exploit spatial information to improve clustering algorithms. In this article, we develop a Bayesian clustering algorithm based on the Dirichlet process prior that uses both genetic and spatial information to classify individuals into homogeneous clusters for further study. We study the performance of our method using a simulation study and use our model to cluster wolverines in Western Montana using microsatellite data.     

A metabolome pipeline: from concept to data to knowledge

Metabolomics, like other omics methods, produces huge datasets of biological variables, often accompanied by the necessary metadata. However, regardless of the form in which these are produced they are merely the ground substance for assisting us in answering biological questions. In this short tutorial review and position paper we seek to set out some of the elements of “best practice” in the optimal acquisition of such data, and in the means by which they may be turned into reliable knowledge. Many of these steps involve the solution of what amount to combinatorial optimization problems, and methods developed for these, especially those based on evolutionary computing, are proving valuable. This is done in terms of a “pipeline” that goes from the design of good experiments, through instrumental optimization, data storage and manipulation, the chemometric data processing methods in common use, and the necessary means of validation and cross-validation for giving conclusions that are credible and likely to be robust when applied in comparable circumstances to samples not used in their generation.This revised version was published online in June 2005. The previous version did not contain colour images.     

一种新的生态监测数据质量评估方法——以CERN乔木生长数据为例

将数据可靠性作为有序变量进行分级,在理论上使数据可靠性与主要生态过程、次级生态过程、外部过程等数据源建立关联,构建了一种生态监测数据质量评估方法,提供了一个新的数据质量指数.它通过观察记录的合格率来估计数据集的质量,其检测结果包括了每一条数据的可靠性级别、标记为离群或错误数据的原因,以及完整数据集的质量指数值.将该方法应用于CERN的两个乔木生长数据集,发现该数据质量指数可以定量评估乔木生长数据集的质量.该方法为相关软件的开发提供了基础.     

Replication of an association of variation in the FOXO3A gene with human longevity using both case–control and longitudinal data

Genetic variation in FOXO3A has previously been associated with human longevity. Studies published so far have been case–control studies and hence vulnerable to bias introduced by cohort effects. In this study we extended the previous findings in the cohorts of oldest old Danes (the Danish 1905 cohort, N = 1089) and middle‐aged Danes (N = 736), applying a longitudinal study design as well as the case–control study design. Fifteen SNPs were chosen in order to cover the known common variation in FOXO3A. Comparing SNP frequencies in the oldest old with middle‐aged individuals, we found association (after correction for multiple testing) of eight SNPs; 4 (rs13217795, rs2764264, rs479744, and rs9400239) previously reported to be associated with longevity and four novel SNPs (rs12206094, rs13220810, rs7762395, and rs9486902 (corrected P‐values 0.001–0.044). Moreover, we found association of the haplotypes TAC and CAC of rs9486902, rs10499051, and rs12206094 (corrected P‐values: 0.01–0.03) with longevity. Finally, we here present data applying a longitudinal study design; when using follow‐up survival data on the oldest old in a longitudinal analysis, we found no SNPs to remain significant after the correction for multiple testing (Bonferroni correction). Hence, our results support and extent the proposed role of FOXO3A as a candidate longevity gene for survival from younger ages to old age, yet not during old age.