Quantifying quantum correlation via quantum coherence

Resource theory is applied to quantify the quantum correlation of a bipartite state and a computable measure is proposed. Since this measure is based on quantum coherence, we present another possible physical meaning for quantum correlation, i.e., the minimum quantum coherence achieved under local unitary transformations. This measure satisfies the basic requirements for quantifying quantum correlation and coincides with concurrence for pure states. Since no optimization is involved in the final definition, this measure is easy to compute irrespective of the Hilbert space dimension of the bipartite state.     

土地资源多级网格平台高效处理机制研究

为实现海量土地资源数据多级网格管理和高效处理,设计了基于网格服务架构的土地资源多级网格化管理平台LR-MGSP（Land Resource Multi-Grid Service Platform）,从网格任务分解、空间信息服务缓存和增量统计等方面探讨了提高平台处理性能的策略和方法.原型平台与非网格化的土地资源管理系统的性能对比测试结果表明,LR-MGSP达到了预期的目标,能够满足海量土地资源数据高效管理和处理的需求,也为其他行业开展跨机构协同处理海量空间数据工作提供了借鉴.     

具有恶化效应和凸资源分配关系的单机排序问题

研究工件加工时间具有恶化效应和凸资源关系的单机排序问题,其中工件的实际加工时间是其正常的加工时间,工件开工时间(具有恶化效应)及消耗资源量的函数。目标为在最大完工时间(总完工时间、总等待时间、完工时间总绝对差与等待时间总绝对差)小于或等于给定常数的条件下找到工件的最优排序和最优的资源分配使工件的总资源消耗量最少。在单机状态下,证明了此问题是多项式时间可解的,并给出了求解该问题的算法和数值实例。     

分布式计算机软件数据整合平台设计

为实现当前经济市场中各应用软件的整合,提高我国各行业间个性化软件的开发能力,加强企业间的科学化系统软件设立,保证企业的高效运行,以及质量和系统维护能力;根据较为常用的分布式计算机系统,提出一种软件数据整合平台的设计;以商用软件整合平台设计为例,以开发模式、服务、技术结构、功能为研究方向,在企业正常运行时,可以实现业务系统功能开发以及门户单点登录,提高企业的个性化系统应用和经济效益;本文根据以上基本需求提出该功能软件平台进行设计,并在实际应用中分析出对于当前企业发展所提供的助力;结果显示,在当前经济发展状况下,有效地使用软件数据整合平台可以很大程度上提高企业的科学化管理和有效的资源分配,使企业在市场竞争中提高经济效益和社会效益。     

精细化工数字化课程教学资源建设

精细化工数字化课程教学资源的使用,不仅可以丰富课程教学资源体系,而且可以使学生的学习和教师的指导不再局限于有限的教室空间和课堂时间,改进学生的学习方式,满足多样化的学习需要,提高学生的学习效率。简单分析了目前精细化工教学中存在的问题与精细化工数字化课程教学资源建设的意义,并介绍了数字化课程教学资源共建的方法与内容。     

基于博弈论的认知无线电网络跨层资源分配

针对多跳认知无线电网络的多层资源分配问题,提出了协作去耦合方法和跨层联合方法,协作去耦合方法首先单独完成路径选择任务,随后进行信道与功率的博弈分配;跨层联合方法则通过博弈直接对路径、信道、功率三层资源进行同时分配,两种方法都综合考虑网络层、介质访问控制层、物理层的启发原则,引入了节点被干扰度信息和节点主动干扰度信息来辅助路径选择,设计了基于功率允许宽度信息的Boltzmann探索来完成信道与功率选择,设计了长链路和瓶颈链路替换消除机制以进一步提高网络性能,从促进收敛角度,选择序贯博弈并设计了具体的博弈过程,此外还分析了博弈的纳什均衡,讨论了两种算法的复杂度,仿真结果表明,协作去耦合方法和跨层联合方法在成功流数量、流可达速率、发射功耗性能指标上均优于简单去耦合的链路博弈、流博弈方法。     

Game theory-based radio resource allocation in NOMA vehicular communication networks supported by UAV

Vehicular communication networks are emerging as a promising technology to provide high-quality internet service such as entertainment for road users via infrastructure-to-vehicle (I2V) communication, and to guarantee road users’ safety via vehicle-to-vehicle (V2V) communication. Some technical issues that impact the performance of these networks are the lack of or poor communication paths between vehicles, and the limitation of radio resources. Unmanned aerial vehicles (UAVs) as promising solutions for supporting vehicular networks could provide communication coverage in hazardous environments and areas with no capacities for installation or maintenance of ground base stations (BSs). Also, non-orthogonal multiple access (NOMA) methods can improve spectral and energy efficiency and thereby allow more users to be connected to the desired network. In this paper, exploring the NOMA, we develop a scheme for optimum resource allocation in presence of a UAV that supports vehicular communications. Resource allocation for this scenario is formulated as a mixed-integer non-linear programming (MINLP) problem. Due to the high complexity of such problems, we propose two low-complexity near-optimal methods. First, we apply difference-of-concave-functions (DC) approximations to solve the problem in an iterative process. Next, we use Stackelberg game-based method for efficient solving, and then, closed-form expressions of optimal power allocations using KKT-conditions are derived. Simulations illustrate the effectiveness of the proposed scheme along with the Stackelberg game-based method.     

不确定环境下服务资源配置优化

在服务资源配置过程中,按维修状态将服务对象分成三类:完全维修、部分维修及最小维修.由于维修服务的特性,服务成本与服务时间均是一个模糊数,并且维修对象在服务时所处的维修状态也具有一定的不确定性.针对这类情况下的服务资源配置问题,提出了同时考虑模糊服务成本和模糊服务时间及不确定维修状态的最小化服务成本为优化指标的服务资源配置模型.在模型的求解过程中采用多粒子群算法,通过仿真计算表明了该方法的可行性和有效性.     

Bandwidth allocation for guaranteed versus best effort service categories

Modern communication networks evolve towards integration of guaranteed-performance and best-effort service types. The coexistence of these two service types offers substantial benefits, such as resource sharing between service classes, and the ability of the user to select an appropriate service class according to its individual requirements and preferences. Notwithstanding, such interaction gives rise to more complicated system behavior and related performance issues, which need to be explored and understood in order to allow efficient network operation. In this paper we examine potential congestion phenomena, which arise due to the combined effect of bandwidth sharing and user migration between service classes. We propose a simplified fluid model for session flow, consisting of two coupled queues with state-dependent flows, which captures the essential ingredients of service-class interaction. Our analysis shows that the system might exhibit bistable behavior, in the sense that transient congestion may stir the system from a stable and efficient operating point to an inefficient and congested one. We identify conditions which give rise to bistability, and propose a call admission control scheme which prevents the system from getting trapped in a congested-type equilibrium, while not interfering with normal system operation. This revised version was published online in June 2006 with corrections to the Cover Date.     

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm is proposed, and a fitness function is provided. Simulations are conducted using the adaptive niche immune genetic algorithm, the simulated annealing algorithm, the quantum genetic algorithm and the simple genetic algorithm, respectively. The results show that the adaptive niche immune genetic algorithm performs better than the other three algorithms in terms of the multi-user cognitive radio network resource allocation, and has quick convergence speed and strong global searching capability, which effectively reduces the system power consumption and bit error rate.