一种面向关键属性更新的优化数据一致性算法

规模巨大且分布性强的P2P系统可能导致部分数据副本发布的更新被长时间地延迟,从而降低Internet上资源定位的效率。针对关键属性更新的特点,提出一种解决关键属性更新冲突的优化数据一致性算法。算法中分离出用户提交的更新请求中关于关键属性的更新,在对关键更新冲突分类的基础上,采用更新缓冲预处理和关键更新表两层机制并结合最新写胜出和分而治之规则,优化关键更新冲突的发现和解决。关键属性更新的优化处理使得不会产生因为关键属性更新的延迟而降低系统基于关键属性的资源定位效率,满足面向Internet的P2P系统的要求。模拟测试结果表明该算法在一致性维护开销、资源定位开销与资源访问开销以及鲁棒性方面均具有较好的性能。     

引入价格因素的网络资源分配模型与算法实现

引入价格因素,针对网络资源分配提出PE-EMRA网络资源分配模型,并给出算法实现。PE-EMRA模型综合考虑带宽、缓冲等多种网络资源,调节并限制各业务类流量,使系统总效率最大化。该方法可有效提高资源利用率,提供服务质量保证,并具有配置灵活、实现代价小等特点。     

被动传感器融合检测系统的优化分布密度

被动传感器由于采用无源探测,而且制造成本低,体积小,在战场环境中将采用并配置大量的被动传感器来检测目标.不论是主动还是被动式传感器,在实际应用中均存在资源优化配置问题.针对被动传感器的具体应用模型,采取了若干合理近似,得到了在"OR"融合检测条件下,基于最大检测概率的被动传感器优化配置密度计算公式.     

面向管理员的网络可生存性建模与计算

从网络系统安全评价和管理的角度出发,紧密结合可生存性定义和可生存性的四个特征属性,建立了面向管理员的网络可生存性量化模型;给出了该模型的算法流程;提出了面向管理员的网络可生存性计算公式,该公式中包括恢复率和系统状态转移矩阵的计算方法,反映出可生存性对网络空闲资源和恢复时间的要求;最后进行了面向管理员的网络可生存性计算的仿真实验,表明可以利用有限的网络资源实现高水平的网络可生存性。     

动态规划在消防增援调度中的应用

由于各消防中队一般规模较小，对于较大规模的火灾需要多个消防队共同救护，此时若能够实现增援调度的最优化可以提高这些同时出现的火灾被全部扑灭的概率。利用多阶段动态规划对增援调度进行了研究，并分析了具体案例。通过分析得出此方法有助于改善消防资源分配状况，以实现最大程度地减小经济损失。     

太空快速响应发射场能力建设

为实现战争行动和突发事件的快速响应目的,太空快速响应发射已成为重要的解决手段。总结传统航天发射场面临的挑战,分析了太空快速响应活动对航天发射场的需求,从发射场建设需求体系、发射场测试能力推进、发射场改造和补充建设、天地一体测控通信体系、快速机动发射模式等提出了发射场建设发展途径,为满足太空快速响应发射场系统建设提供有益的技术参考。     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.     

面向计算流体力学的图形处理器资源管理

针对求解计算流体力学过程中图形处理器资源利用率低的问题,提出面向计算流体力学的图形处理器资源优化管理方案。基于计算流体力学的算法特性和同时运行任务的执行特点,设计合理的调度方案。通过动态改变不同任务的启动规模和启动时间,在减少资源竞争的同时提高图形处理器资源的有效使用。实验结果表明:本文提出的资源管理方案相比基线方法在不同任务规模下的平均加速比达到 1.64,对图形处理器的硬件资源使用也有了显著的提升。     

云计算安全协议设计

分析了目前云计算服务中存在的应用风险和安全隐患,并将其抽象为两方面的问题,即安全边界问题和用户服务资源映射问题。为了解决这两个方面的问题,根据云计算系统的实际需求,给出云计算服务的一种普适性的定义;在此定义基础上,提出了云计算服务的安全框架,并设计了云计算服务各层协议集合。在这个框架和协议集合下,分析了保证云计算服务正常执行所需的四方面要素,以及将诸要素较好地整合在一起的方法。     

Revenue management with aircraft reassignment flexibility

A well‐studied problem in airline revenue management is the optimal allocation of seat inventory among different fare‐classes, given a capacity for the flight and a demand distribution for each class. In practice, capacity on a flight does not have to be fixed; airlines can exercise some flexibility on the supply side by swapping aircraft of different capacities between flights as partial booking information is gathered. This provides the airline with the capability to more effectively match their supply and demand. In this paper, we study the seat inventory control problem considering the aircraft swapping option. For theoretical and practical purposes, we restrict our attention to the class of booking limit policies. Our analytical results demonstrate that booking limits considering the swapping option can be considerably different from those under fixed capacity. We also show that principles on the relationship between the optimal booking limits and demand characteristics (size and risk) developed for the fixed‐capacity problem no longer hold when swapping is an option. We develop new principles and insights on how demand characteristics affect the optimal booking limits under the swapping possibility. We also develop an easy to implement heuristic for determining the booking limits under the swapping option and show, through a numerical study, that the heuristic generates revenues close to those under the optimal booking limits. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011