基于云计算的物联网数据挖掘

物联网是一个巨大的、分布广泛的物与物相连的网络,其上产生的海量数据通常是与时间和空间相关的,具有动态、异构、分布的特性,因此对这些数据的挖掘非常困难,而且耗费时间和内存,效率低下。为了解决这些问题,提出了一种基于云计算的物联网数据挖掘系统:将这些海量数据转化为PML数据文件,并存储在HDFS中,同时把挖掘任务分配到多台节点服务器上并行处理。采用Hadoop平台,将关联规则Apriori算法Map/Reduce化,提高了挖掘的效率。另外,采用副本策略将计算向存储迁移,将失效节点的计算迁移到副本数据存储节点就地执行,降低了数据传输的时间,大为提高了挖掘的效率。     

基于三点估计法的直流配电中心概率潮流计算

分布式电源呈间歇性/波动性,负荷呈随机性,利用概率统计理论研究基于不确定性量的电力系统规划、运行与控制已成为当前的研究热点。针对近年来不断增加的以风电、光伏为代表的分布式电源接入柔性直流配电网的现象,开展了概率潮流研究。以Nataf变换方法结合Cholesky分解进行不确定变量的相关性处理,提出了一种计及输入变量相关性的三点估计法的柔性直流配电网概率潮流计算方法;以国内首个五端柔性直流配电示范工程—直流配电中心作为算例,建立了基于三点估计法的统一直流概率潮流计算模型,计算结果验证了该算法的有效性和合理性。     

关于加快发展南通市家用纺织业的思考

立足国内家用纺织品发展的大环境,在重点考察了南通、上海、无锡等地家用纺织业现状的基础上,就加快南通家用纺织业的发展提出了打造“南通国际家用纺织品研发（设计）中心”的具体思路。     

基于MetaFrame的中小企业ASP服务平台解决方案*

介绍了ASP模式的概念、优点,分析了MetaFrame的技术特点及基于服务器计算体系结构。在此基础上提出了一套基于MetaFrame的中小企业ASP服务平台解决方案,并给出具体的应用示例。     

Detecting similarities in virtual machine behavior for cloud monitoring using smoothed histograms

The growing size and complexity of cloud systems determine scalability issues for resource monitoring and management. While most existing solutions consider each Virtual Machine (VM) as a black box with independent characteristics, we embrace a new perspective where VMs with similar behaviors in terms of resource usage are clustered together. We argue that this new approach has the potential to address scalability issues in cloud monitoring and management. In this paper, we propose a technique to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. This innovative technique models VMs behavior exploiting the probability histogram of their resources usage, and performs smoothing-based noise reduction and selection of the most relevant information to consider for the clustering process. Through extensive evaluation, we show that our proposal achieves high and stable performance in terms of automatic VM clustering, and can reduce the monitoring requirements of cloud systems.     

Cloud based intelligent system for delivering health care as a service

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity.     

Hybrid shuffled frog leaping algorithm for energy-efficient dynamic consolidation of virtual machines in cloud data centers

Cloud computing aims to provide dynamic leasing of server capabilities as scalable virtualized services to end users. However, data centers hosting cloud applications consume vast amounts of electrical energy, thereby contributing to high operational costs and carbon footprints. Green cloud computing solutions that can not only minimize the operational costs but also reduce the environmental impact are necessary. This study focuses on the Infrastructure as a Service model, where custom virtual machines (VMs) are launched in appropriate servers available in a data center. A complete data center resource management scheme is presented in this paper. The scheme can not only ensure user quality of service (through service level agreements) but can also achieve maximum energy saving and green computing goals. Considering that the data center host is usually tens of thousands in size and that using an exact algorithm to solve the resource allocation problem is difficult, the modified shuffled frog leaping algorithm and improved extremal optimization are employed in this study to solve the dynamic allocation problem of VMs. Experimental results demonstrate that the proposed resource management scheme exhibits excellent performance in green cloud computing.     

一种基于固件的云系统策略文件完整性安全机制

针对云系统服务器之间共享策略文件所面临的完整性安全威胁,提出一种新的基于固件的策略安全机制。该机制可在云系统服务器平台之间安全且快速地进行共享策略文件交互,并可对共享策略文件进行完整性校验,进而提高协同工作的服务器所共享策略文件的安全性。实验结果表明,该机制有效实现了云系统环境下共享策略文件的完整性安全,同时提高了云系统管理员的管理效率。     

一种基于点集拓扑分形变幻的云计算登录认证方法

考虑到云服务登录安全性及便捷性的需求,针对单点登录认证模式,提出云计算的统一登录认证方法,并采用点集拓扑分形变幻方法生成随机密钥,提高登录认证的安全等级。首先对云计算登录认证系统结构进行分析,然后以网络公共数据库中的指纹图像为例,进行分形变幻环运算,生成伪随机序列,再将这些序列加密并通过UDP发送给服务器端进行认证,最后进行实例仿真。     

基于PBIL算法的物流中心选址问题研究

介绍了基于种群竞争式学习的PBIL算法的基本原理和实现方法。比较了PBIL算法和遗传算法求解过程的异同点。分析了PBIL算法在物流中心选址问题中的应用,并且通过实例验证了算法的可行性和有效性,证明了PBIL算法比遗传算法具有更高的搜索效率。