Trusted Grid Computing with Security Binding and Trust Integration

Trusted Grid computing demands robust resource allocation with security assurance at all resource sites. Large-scale Grid applications are being hindered by lack of security assurance from remote resource sites. We developed a security-binding scheme through site reputation assessment and trust integration across Grid sites. We do not treat the trust factor deterministically. Instead, we apply fuzzy theory to handle the fuzziness or uncertainties behind all trust attributes. The binding is achieved by periodic exchange of site security information and matchmaking to satisfy user job demands. PKI-based trust model supports Grids in multi-site authentication and single sign-on operations. However, cross certificates are inadequate to assess local security conditions at Grid sites. We propose a new fuzzy-logic trust model for distributed trust aggregation through fuzzification and integration of security attributes. We introduce the trust index of a Grid site, which is determined by site reputation from its track record and self-defense capability attributed to the risk conditions and hardware and software defenses deployed at a Grid site. A Secure Grid Outsourcing (SeGO) system is designed for secure scheduling a large number of autonomous and indivisible jobs to Grid sites. Significant performance gains are observed after trust aggregation, which is evaluated by running scalable NAS and PSA workloads over simulated Grids. Our security-binding scheme scales well with increasing user jobs and Grid sites. The new scheme can guide the security upgrade of Grid sites and predict the Grid performance of large workloads under risky conditions. The research work reported here was supported by a NSF ITR Grant 0325409. The paper is significantly extended from preliminary results presented in IFIP International Conference on Network and Parallel Computing (NPC-2004), IEEE International Parallel and Distributed Processing Symposium (IPDPS-2005), and International Workshop on Grid Security and Resource Management (GSRM-2005). The corresponding author is Kai Hwang at the University of Southern California.  

A perturbed particle swarm algorithm for numerical optimization

The canonical particle swarm optimization (PSO) has its own disadvantages, such as the high speed of convergence which often implies a rapid loss of diversity during the optimization process, which inevitably leads to undesirable premature convergence. In order to overcome the disadvantage of PSO, a perturbed particle swarm algorithm (pPSA) is presented based on the new particle updating strategy which is based upon the concept of perturbed global best to deal with the problem of premature convergence and diversity maintenance within the swarm. A linear model and a random model together with the initial max–min model are provided to understand and analyze the uncertainty of perturbed particle updating strategy. pPSA is validated using 12 standard test functions. The preliminary results indicate that pPSO performs much better than PSO both in quality of solutions and robustness and comparable with GCPSO. The experiments confirm us that the perturbed particle updating strategy is an encouraging strategy for stochastic heuristic algorithms and the max–min model is a promising model on the concept of possibility measure.  

带时间窗的粮食物流车辆路径问题的研究

带时间窗的粮食物流车辆路径问题是一个典型的NP—难问题。针对粮食物流批量大、多点对多点等特点,建立了带时间窗的粮食物流车辆路径问题(Vehicle Routing Problem with Time Windows,VRPTM)的数学模型,进一步构造粒子群算法(Particle Swarm Optimization,PSO)用于问题求解,并将求解结果与遗传算法进行比较。结果表明,粒子群算法可以快速、有效地求得带时间窗的粮食物流车辆路径问题的优化解,降低配送成本。  

PLC在变压吸附系统中的设计与实现

提出了以FX2N128MR超小型可编程控制器为核心,构建PSA硬件系统的设计方案,实现了制氢生产中变压吸附装置的开关量输入、输出和报警联锁控制。在工艺时序表和硬件系统基础上进行编程,实现了对现场的过程控制。  

PLC在变压吸附系统中的设计与实现

提出了以FX2N 128MR超小型可编程控制器为核心，构建PSA硬件系统的设计方案．实现了制氢生产中变压吸附装置的开关量输入、输出和报警联锁控制。在工艺时序表和硬件系统基础上进行编程，实现了对现场的过程控制。  

金免疫层析试条PSA测定系统的研究

前列腺特异性抗原PSA(Prostate Specific Antigen,PSA)对早期前列腺癌的诊断具有敏感性和特异性。本文主要介绍了金免疫层析试条的PSA测定系统。该测定系统实现了光电检测、信号综合处理、保存、显示PSA浓度、打印检测报告等功能。  

基于单片机的制氧控制系统

通过本控制系统的研究,实现PSA系列医用制氧设备的集成化和智能化控制,为我军提供高效的智能型医用制氧设备。本控制系统是以PSA医用制氧设备为控制对象,根据分子筛变压吸附(PSA)制氧技术及其总体方案来确立的,并通过LPC935系列单片机来实现。试制结果表明,该控制方案是有效的。  

高级综合十年进展

介绍EDA领域中的一个重要方向高级综合最近十年的进展情况,并对以前的工作做了简单的回顾.对各个有代表性的算法进行了描述,并且对这些算法的基本思路进行了分析和总结.对最近出现的一些新的研究热点也进行了阐述和分析,并对以后的发展做了一个展望.提出了一些待研究解决的问题.  

Bayesian piecewise mixture model for racial disparity in prostate cancer progression

Racial differences in prostate cancer incidence and mortality have been reported. Several authors hypothesize that African Americans have a more rapid growth rate of prostate cancer compared to Caucasians, that manifests in higher recurrence and lower survival rates in the former group. In this paper we propose a Bayesian piecewise mixture model to characterize PSA progression over time in African Americans and Caucasians, using follow-up serial PSA measurements after surgery. Each individual’s PSA trajectory is hypothesized to have a latent phase immediately following surgery followed by a rapid increase in PSA indicating regrowth of the tumor. The true time of transition from the latent phase to the rapid growth phase is unknown, and can vary across individuals, suggesting a random change point across individuals. Furthermore, some patients may not experience the latent phase due to the cancer having already spread outside the prostate before undergoing surgery. We propose a two-component mixture model to accommodate patients both with and without a latent phase. Within the framework of this mixture model, patients who do not have a latent phase are allowed to have different rates of PSA rise; patients who have a latent phase are allowed to have different PSA trajectories, represented by subject-specific change points and rates of PSA rise before and after the change point. The proposed Bayesian methodology is implemented using Markov Chain Monte Carlo techniques. Model selection is performed using deviance information criteria based on the observed and complete likelihoods. Finally, we illustrate the methods using a prostate cancer dataset.  

基于Visio平台的故障树自动建模软件开发

故障树分析(FTA)是概率安全评价方法(PSA)的主要方法,故障树建模则是整个分析过程最基本也是最繁琐的一个过程。而PSA主要应用在对可靠性要求极高的系统上,诸如航天航海系统和核电厂数字化仪控系统。这类系统往往规模大、结构复杂、相关性高,对其进行故障树建模的工作艰巨而繁琐。人为完成将会耗费大量人力物力,且正确性无法保障。通过开发故障树自动建模软件,使故障树建模过程自动化,减少PSA分析的前期准备时间,提高PSA分析的效率,降低人因失误的概率。