MORM: A Multi-objective Optimized Replication Management strategy for cloud storage cluster

Effective data management is an important issue for a large-scale distributed environment such as data cloud. This can be achieved by using file replication, which efficiently reduces file service time and access latency, increases file availability and improves system load balancing. However, replication entails various costs such as storage and energy consumption for holding replicas. This article proposes a multi-objective offline optimization approach for replica management, in which we view the various factors influencing replication decisions such as mean file unavailability, mean service time, load variance, energy consumption and mean access latency as five objectives. It makes decisions of replication factor and replication layout with an improved artificial immune algorithm that evolves a set of solution candidates through clone, mutation and selection processes. The proposed algorithm named Multi-objective Optimized Replication Management (MORM) seeks the near optimal solutions by balancing the trade-offs among the five optimization objectives. The article reports a series of experiments that show the effectiveness of the MORM. Experimental results conclusively demonstrate that our MORM is energy effective and outperforms default replication management of HDFS (Hadoop Distributed File System) and MOE (Multi-objective Evolutionary) algorithm in terms of performance and load balancing for large-scale cloud storage cluster.     

Online double auction mechanism for perishable goods

One-sided auctions are used for market clearing in the spot markets for perishable goods because production cost in spot markets is already “sunk.” Moreover, the promptness and simplicity of one-sided auctions are beneficial for trading in perishable goods. However, sellers cannot participate in the price-making process in these auctions. A standard double auction market collects bids from traders and matches the higher bids of buyers and lower bids of sellers to find the most efficient allocation, assuming that the value of unsold items remains unchanged. Nevertheless, in the market for perishable goods, sellers suffer a loss when they fail to sell their goods, because their salvage values are lost when the goods perish. To solve this problem, we investigate the suitable design of an online double auction for perishable goods, where bids arrive dynamically with their time limits. Our market mechanism aims at improving the profitability of traders by reducing trade failures in the face of uncertainty of incoming/departing bids. We develop a heuristic market mechanism with an allocation policy that prioritizes bids of traders based on their time-criticality, and evaluate its performance experimentally using multi-agent simulation. We find out that our market mechanism realizes efficient and fair allocations among traders with approximately truthful behavior in different market situations.     

实例依赖的可验证随机函数的高效构造*

实例依赖的可验证随机函数是由文献[1]提出的一个新的密码学概念,它也是构造高安全性的零知识协议（如可重置零知识论证系统）的一个强有力的工具,而这些高安全性的零知识协议在智能卡和电子商务中有着重要的潜在价值。基于非交互ZAP证明系统和random oracle模型中∑OR-协议,给出了实例依赖的可验证伪随机函数的两个高效的实现和相应的安全性证明,提升了这一工具的应用价值。     

Optimization of satellite searching strategy of the non-stationary antenna

The tiny searching step length and the satellite distribution density are the major factors to influence the efficiency of the satellite finder, so a scientific and reasonable method to calculate the tiny searching step length is proposed to optimize the satellite searching strategy. The pattern clustering and BP neural network are applied to optimize the tiny searching step length. The calculated tiny searching step length is approximately equal to the theoretic value for each satellite. In application, the satellite searching results will be dynamically added to the training samples to re-train the network to improve the generalizability and the precision. Experiments validate that the optimization of the tiny searching step length can avoid the error of locating target satellite and improve the searching efficiency.     

高速旋转实验机关键设计技术的研究

详细分析了高速旋转设备的工作特点，对旋转实验机的传动系统连接方式、轴承配合形式以及过载保护装置的结构射进等关键技术进行了全面地研究，分析了影响实验机正常工作的主要因素，并结合分析结果设计了适合旋转实验机实际工作的执行机构。     

Factors influencing health care professionals’ adoption of mobile platform of medical and senior care in China

A mobile platform of medical and senior care (MPMSC) is a platform that can provide one-stop medical and senior care services through mobile devices. This study developed a research model based on the value-based adoption model to understand the factors influencing health care professionals’ adoption of MPMSC. Empirical analysis has shown that perceived value and legal concerns can predict health care professionals’ intention to adopt MPMSC and that outcome expectations, perceived mobility, perceived effort, and privacy concerns can predict perceived value. Research findings can enhance the understanding of the factors influencing the adoption of MPMSC by health care professionals.     

一种标准模型下的强指定验证者签名方案

强指定验证者签名方案(SDVS)能让指定的接收方确认消息发送方的身份, 但不能向第三方证明发送方的身份, 在电子商务和电子政务中有广泛应用. 在DBDH问题和Gap BDH问题困难的前提下, 利用双线性对, 构造了基于身份的强指定验证者签名方案, 并在标准模型下证明了方案的安全性. 分析结果表明新提出的方案具有签名者身份的隐私性、不可传递性以及对签名验证的不可委托性. 该方案使用双线性对, 不需要证书, 可简化密钥管理; 其通信和计算效率高, 实现简单, 可用于计算能力受限的设备.     

一种基于死区离散趋近律的准滑模控制

针对受正弦信号干扰的不确定离散时间系统,提出一种基于死区离散趋近律的准滑模控制方法. 系统能够由任一初始状态向死区作单调趋近运动,并于有限时间到达准滑动模态区作准滑动模态运动. 准滑动模态带具有任意阶次小的特点.该方法进一步增强了系统鲁棒性,有效改善系统动态品质,减小了稳态误差.系统无 控制抖振和稳态抖振产生.仿真结果表明该方法的有效性.     

突发事件应急管理情景分析:宏观审视与微观解构

风险社会背景下，可预见和难以预见的风险因素明显增多，对我国应急管理体系和应急管理能力的现代化提出了更高要求。情景分析是对不确定性的未来进行研究的分析方法和实践工具，与突发事件应急管理中对不确定性因素的分析具有高度契合性。以突发事件应急管理情景分析为研究对象，运用CiteSpace软件绘制知识图谱，宏观审视应急管理情景分析研究的趋势与规律；微观上从理论修正与拓展、流程调整与规范、方法应用与实践三方面解构应急管理情景分析研究的内容与热点。结果表明:突发事件应急管理情景分析尚未形成清晰的研究主线，但具有较大潜力；研究内容呈现出多元化特征，但本土化研究相对较缺乏；当前研究不能满足实践需要，重大突发事件高度复杂性倒逼情景分析研究。     

明代紫禁城营建石材采办述略

明初永乐迁都北京,开始营建宫殿城池,其中紫禁城营建规模宏大,且历朝修缮.石材作为基础建筑材料,在紫禁城营建过程中得到广泛应用.为满足营建工程对石材的巨大需求,明政府开始了大规模的石材采办活动.本文阐述了紫禁城营建工程所需石材的产地、开采和运输过程,以当时探求石材采办之过程.