知识的通信资源管理决策支持系统

专家系统可以模拟专家分析和解决问题的过程进行推理,最终给出合理的方案.将人工智能技术引入通信资源管理,提出了基于知识的通信资源管理方法,讨论了基于该方法的通信资源管理决策支持系统体系结构、知识库资源优化和推理机制.     

一种基于层次位线缓冲的异步片上路由器

片上缓存资源是片上路由器的重要组成部分,其结构好坏直接关系到片上互联网络的实现复杂度、整体性能及功耗开销。鉴于异步电路的握手工作方式,异步路由器一般采用基于移位寄存器的异步FIFO(First In First Out)实现片上缓冲,这种结构导致了报文传输延迟及数据翻转次数增加。提出一种基于层次位线缓冲的异步FIFO结构,设计实现了一种新的异步路由器结构。相对于传统异步路由器,新的异步路由器能够有效降低路由器设计的硬件复杂度,减少数据的冗余翻转,降低功耗。实验结果表明在相同配置的情况下,新异步路由器面积降低了39.3%;当异步FIFO深度为8的时候,新异步路由器能够获得41.1%的功耗降低。     

光互连网络中资源预留的多级光互连仲裁机制

基于资源预留策略提出一种多级光互连仲裁机制,通过将网络分级实现快速、高效的仲裁。多优先级数据缓存队列的传输节点设计,提供了不同类型流量的差异化传输;通过预约式两级仲裁机制,实现网络的完全公平与100%的高吞吐率。设计并对快速仲裁通道进行了合理布局,极大地缩短了仲裁延迟。仿真结果表明:采用基于资源预留的分级仲裁策略,在多种流量模式下所有节点均获得公平的服务。与Feather Weight相比,分级仲裁策略吞吐率提高17%;与2-pass相比,仲裁延迟减少15%,同时,功耗减少5%。     

蜂窝网络中基于干扰控制的D2D通信联合资源分配方案

在蜂窝网络中部署D2D(Device-to-Device)通信能够有效提升频谱利用率,降低基站负载,但D2D用户与蜂窝用户共享无线信道时会产生信号干扰。提出了一种联合资源分配算法,通过综合考虑信道分配对网络中已有的蜂窝用户和D2D用户的信号干扰,并在小区范围内寻找具有最小干扰值的信道资源分配给用户,以实现有效的干扰控制。仿真结果显示:联合资源分配能够提升D2D链路、蜂窝链路的信噪比及系统总吞吐量,使得蜂窝网络的整体性能优于独立资源分配。     

空投着陆缓冲系统效能评估模型

为了有效构建空投缓冲系统效能评估体系,研究建立了不同缓冲系统通用效能评估模型。模型综合分析缓冲系统作战能力与保障能力,建立了空投缓冲系统效能指标体系。在此基础上,运用效能评估ADC模型与AHP方法,结合指标能力量化准则实现对缓冲系统效能的定量评定。通过实例计算,验证了模型的正确性和有效性,为缓冲系统的发展论证与使用决策提供依据。     

基于Multi-agent协商的多干扰机资源管理

多干扰机协同是组网雷达对抗的一种重要方法。针对多干扰机协同中面临的数据传输率、时效性等因素所引起的干扰资源管理问题,建立了基于中心控制协商和公约协商的干扰资源管理模型,并给出了相应的协同算法与仿真。仿真结果表明：两种方法在组网雷达对抗中均能取得良好的干扰效果及较低的漏威胁目标信号脉冲比例。其中,基于公约的Multi?agent协商在组网干扰资源管理方面具有更好的可行性,其效果优于基于中心控制协商的方法。     

A self‐adapting genetic algorithm for project scheduling under resource constraints

This papers deals with the classical resource‐constrained project scheduling problem (RCPSP). There, the activities of a project have to be scheduled subject to precedence and resource constraints. The objective is to minimize the makespan of the project. We propose a new heuristic called self‐adapting genetic algorithm to solve the RCPSP. The heuristic employs the well‐known activity list representation and considers two different decoding procedures. An additional gene in the representation determines which of the two decoding procedures is actually used to compute a schedule for an individual. This allows the genetic algorithm to adapt itself to the problem instance actually solved. That is, the genetic algorithm learns which of the alternative decoding procedures is the more successful one for this instance. In other words, not only the solution for the problem, but also the algorithm itself is subject to genetic optimization. Computational experiments show that the mechanism of self‐adaptation is capable to exploit the benefits of both decoding procedures. Moreover, the tests show that the proposed heuristic is among the best ones currently available for the RCPSP. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 433–448, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10029     

装备维修资源优化中的模拟退火遗传算法

在对模拟退火遗传算法改进的基础上,结合建立的通信装备维修资源分配模型,给出了该算法的实现过程,并利用此算法对模型进行了最优化求解。实例的计算结果表明该算法对于模型的求解具有较好的收敛性。     

分层分布式分群监控体系下的网格资源发现机制

网格中资源发现机制是把资源提供者和资源请求者联系起来的重要环节.在分析分层分布式分群监控体系结构和现有资源发现机制的基础上,提出将集中式目录服务、资源路由表和移动代理三种机制相结合的网格资源发现机制.实验验证该机制在小范围内查找具有性能高效的特点,而在大范围内查找减少了资源发现代理的分发数量,降低了系统消息的负载,进而降低了网络资源的占用.     

A model to design recreational boat mooring fields

This article develops a mathematical model and heuristic algorithm to design recreational boating mooring fields. The boating industry is important to the Florida economy, and boat storage is becoming a concern among those in the industry. The mooring field design problem is formulated to maximize the total number of boat feet moored in the mooring field. In the model, we allow two adjacent moorings to overlap, which introduces a risk that under certain conditions the boats on these moorings could contact each other. We identify the conditions when contact is possible and quantify the probability of contact. The mooring field design problem is formulated as a nonlinear mixed‐integer programming problem. To solve the problem, we decompose it into two separate models, a mooring radii assignment model and a mooring layout model, which are solved sequentially. The first is solved via exhaustive enumeration and the second via a depth‐first search algorithm. Two actual mooring fields are evaluated, and in both cases our model leads to better layouts than ones experts developed manually. The mooring field design model rationalizes the mooring field design and shows that in one case by increasing the risk from 0 to 1%, the mooring efficiency increases from 74.8% to 96.2%. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009