基于蚁群算法的云计算联盟资源调度

针对目前云计算联盟的架构和单云环境下资源调度的研究缺少对云计算联盟下的资源调度问题的研究情况,建立了由云用户、云服务供应商和云联盟协调器组成的云计算联盟资源调度模型,为达到云供应商利益最大化,设计了任务-虚拟机-数据中心的调度算法,利用蚁群算法进行模型求解,并通过Cloudsim仿真软件证实了该算法的合理性,验证了供应商资源的数据中心负载率在60％～80％之间时达到均衡,并可获得最大利益。     

用户利益最大化的云计算联盟资源调度

针对云联盟的资源调度问题进行了研究,提出了基于用户利益最大化的云计算联盟资源调度方法,并通过遗传算法实现资源调度策略。同时基于CloudSim实现了云计算联盟资源调度方法,对云计算联盟环境下的资源调度研究从学术走向实际应用具有一定的意义。     

基于动态联盟的一种身份信任计算模型

在动态联盟中,身份管理是确保信息安全的一种手段,但是随着联盟成员数日益增多,传统的身份管理难以妥善应对当前较为复杂的环境,尤其当成员之间无交互历史时,数据交换的可靠性无法保障。文中研究了不同计算环境中的多种信任管理方法,并把P2P的推荐评价机制应用到动态联盟的身份管理中,提出了一种基于推荐的身份信任管理的算法。在这种算法中,身份的信任值由多因素加权综合而成,其中推荐信任值在算法中起到关键的作用。该算法试图为解决复杂的动态联盟环境下的身份管理问题提供一种途径。     

基于HLA的雷达探测能力仿真系统设计

以对空情报雷达探测系统为研究对象,提出了基于HLA的对空情报雷达探测能力仿真结构。以高层体系结构作为技术框架,分析了仿真系统的特点和实现功能,设计了联邦对象并实现了联邦开发,组建了分布式仿真系统结构。     

基于HLA的陆军分队作战仿真系统研究

高层体系结构（HLA）仿真体系结构是分布式仿真系统研究的重点和热点,在军事仿真领域有着广泛的应用前景。为此首先对基于HLA的陆军分队作战仿真系统进行了总体设计,提出了系统仿真的框架结构,具体介绍了系统联邦成员的构成及功能,并对联邦主要成员进行了对象类、交互类以及相关属性和参数设计,最后给出了整个系统的仿真流程及主要关键代码实现。实验表明,该仿真系统设计能够满足分队作战模拟的需求,为分队训练和作战理论研究提供了研究平台。     

基于HLA的海航作战仿真系统设计研究

首先对基于高层体系结构（HLA）的海航作战仿真系统进行了介绍和分析,在分析作战特点的基础上,依据HLA的体系结构规范,构建了海航作战仿真系统的体系结构框架,并利用统一建模语言（UML）,完成了系统对象类和交互类模型设计,研究了仿真成员代码实现的方法,对航空兵作战仿真的进一步研究和系统开发具有一定的借鉴意义。     

基于HLA的防空导弹营火力仿真系统设计

根据当前空防对抗系统的组成及特点,在建立某型防空导弹营火力仿真系统实体模型的基础上,结合以往项目开发经验,简化联邦开发与执行模型,研究基于UML的HLA开发过程,分4步对仿真系统联邦进行设计和实现。针对目前仿真系统可信度校验难度大的问题,构建该仿真系统的可信度评估层次模型,设计一种基于最优传递矩阵和三角模糊数的层次分析法,既可避免人为主观因素的影响,又可保证评估过程高效性。仿真实验结果表明,该系统高效可信,节省训练经费,为防空导弹分队火力单元的部署和作战效能的改进提供辅助决策手段。     

Real-time data analytics and event detection for IoT-enabled communication systems

Enterprise Communication Systems are designed in such a way to maximise the efficiency of communication and collaboration within the enterprise. With users becoming mobile, the Internet of Things (IoT) can play a crucial role in this process, but is far from being seamlessly integrated into modern online communications. In this paper, we present a semantic infrastructure for gathering, integrating and reasoning upon heterogeneous, distributed and continuously changing data streams by means of semantic technologies and rule-based inference. Our solution exploits semantics to go beyond today’s ad-hoc integration and processing of heterogeneous data sources for static and streaming data. It provides flexible and efficient processing techniques that can transform low-level data into high-level abstractions and actionable knowledge, bridging the gap between IoT and online Enterprise Communication Systems. We document the technologies used for acquisition and semantic enrichment of sensor data, continuous semantic query processing for integration and filtering, as well as stream reasoning for decision support. Our main contributions are the following, (i) we define and deploy a semantic processing pipeline for IoT-enabled Communication Systems, which builds upon existing systems for semantic data acquisition, continuous query processing and stream reasoning, detailing the implementation of each component of our framework; (ii) we present a rich semantic information model for representing and linking IoT data, social data and personal data in the Enterprise Communication scenario, by reusing and extending existing standard semantic models; (iii) we define and develop an expressive stream reasoning component as part of our framework, based on continuous query processing and non-monotonic reasoning for semantic streams, (iv) we conduct experiments to comparatively evaluate the performance of our data acquisition and semantic annotation layer based on OpenIoT, and the performance of our expressive reasoning layer in the scenario of Enterprise Communication.     

The aDORe federation architecture: digital repositories at scale

The need to federate repositories emerges in two distinctive scenarios. In one scenario, scalability-related problems in the operation of a repository reach a point beyond which continued service requires parallelization and hence federation of the repository infrastructure. In the other scenario, multiple distributed repositories manage collections of interest to certain communities or applications, and federation is an approach to present a unified perspective across these repositories. The high-level, 3-Tier aDORe federation architecture can be used as a guideline to federate repositories in both cases. This paper describes the architecture, consisting of core interfaces for federated repositories in Tier-1, two shared infrastructure components in Tier-2, and a single-point of access to the federation in Tier-3. The paper also illustrates two large-scale deployments of the aDORe federation architecture: the aDORe Archive repository (over 100,000,000 digital objects) at the Los Alamos National Laboratory and the Ghent University Image Repository federation (multiple terabytes of image files).     

新一代装备指挥训练模拟系统总体分析与设计

以我军在未来高技术条件下诸军兵种联合作战对装备指挥训练模拟系统的建设需求为牵引,以装备保障业务规范化为基础,以基于智能主体Agent的高层体层结构HLA为系统建模途径,以Agent联邦为系统运行方式,以智能信息处理为主线,构建我军新一代装备指挥训练平台;并对平台的总体结构、设计思想、系统构建方式和实现技术途径进行了分析。