无线传感器网络中基于效用模型的分布式功率控制机制

本文将效用模型引入无线传感器网络的功率控制设计中,提出了一种基于效用模型的分布式功率控制机制(简称UMDPC).该机制建立了网络中所有传感器节点的功率与效用模型的对应关系,将链路可靠性、网络能耗归纳到统一的网络效用优化框架中,并证明该效用优化问题是凸优化问题,构造基于对偶分解的分布式的优化算法,获得网络效用最大化条件下各节点的优化发射功率.最后,通过模拟实验对所提机制及其实现算法的性能进行比较和评价.实验结果表明,本文所提机制最大化了网络的效用,提高了网络的能量利用效率.     

基于动态资源预测的模糊最小相对容量损失路由算法

提出了一种适用于波分复用光网络的模糊最小相对容量损失路由模型及算法.该算法能够基于不完全的网络状态信息作出路由判断,从而减少对整个网络状态信息的需求.在此算法中,我们提出了层状态信息处理规则和模糊化的网络状态信息模型,使得该路由算法具有一定的动态资源预测的能力,并深入探讨了模糊最小相对容量损失的路由选择及性能优化原则.通过仿真试验表明,我们提出的基于层状态信息处理规则的模糊最小相对容量损失路由算法的性能与基于全网状态信息下的耗尽算法EA(exhaustive algorithm)和最小阻塞算法 LCP(least-congested-path)非常接近.当网络负载较重时,在单位信息量下的网络阻塞性能要优于EA和LCP路由.这说明与其他己知算法相比,模糊最小相对容量损失路由算法更适用于不完全状态信息下的负载较重的网络路由.     

无线mesh网络中基于效用最优的覆盖多播策略

支持多播通信是无线mesh网络(WMN)的一个重要应用.采用基于效用的定价机制,通过拉格朗日(Lagrange)对偶分解法获得一个基于价格的分布式算法.以该分布式算法为核心作为无线mesh网络中数据流速率和功率调整的优化策略,每条链路根据自己转发流所消耗功率状况合理地定价,通过价格机制来调节数据流的速率,从而调整节点接收数据流的速率,使网络净效用最大化.实验结果表明该算法是有效可行的.     

基于最小变量的B-样条移动机器人路径规划研究

为解决移动机器人在避障时的曲线优化问题,提出了基于最小变量的B-样条路径规划方法.对该方法从数学模型上进行了推导,指出了该方法相对于其它B-样条方法的优点,并对该方法进行了优化,给出了相应的优化算法.研究表明:具有最小变量的B-样条函数比只用B-样条函数定义的曲线具有更优化的线性约束,其曲线具有更好的光滑性.     

基于功率和倾角联合优化的小区中断补偿机制

为了实现对中断小区的自主补偿,该文基于自组织网络(SON)提出功率和倾角联合优化调整的小区中断补偿(COC)机制。首先以天线倾角和发射功率作为优化对象,然后对COC定义了合理的优化目标及评价指标,并对优化模型进行分析,最终给出基于遗传优化算法的补偿机制。在分时长期演进(TD-LTE)场景中进行仿真验证,该机制与参考文献中的3种算法相比,在覆盖、干扰和吞吐量等方面均有明显的改善。     

Ad Hoc网络先应式路由维护机制的优化模型研究

Ad Hoc网络先应式路由算法(Proactive Routing Algorithm)具有寻由时延小,拓扑维护及时的优点,适合在网络负载较大的环境下高效运行.本文针对路由维护机制,以减少协议开销和寻由错误报文为目标,提出了基于Ad Hoc网络的先应式路由维护机制优化模型.通过对优化模型的相关参数讨论,得出如下结论:1.先应式路由协议的最优更新时间周期具有"逆向稳定性";2.节点数目n与更新系数h有比例关系n→h^3/2.通过模型求解和仿真结果相比较,验证了模型的正确性.优化模型的研究为先应式路由算法更新机制和算法的可扩展性支持提供了理论依据.     

一个基于多策略的IP-DiffServ业务量工程实现机制研究

提出了一个IP-DiffServ网络业务量工程实现机制,它通过资源分析算法为一个PHB路由定义一条优化路由,通过QoS分析算法为用户业务定义一个优化的PHB,通过在两个算法中应用性能策略、价格策略和负载均衡策略,不但可以提高IP网络提供业务的性能价格比,同时使网络负载和网络资源达到三维均衡分布.实验结果很好地证明机制的优点.     

40Gb/s光纤通信系统中自适应判决反馈均衡器的补偿性能

数值仿真了40Gbit/s 非归零码(NRZ)光纤通信系统中,基于最小均方差算法的非线性自适应判决反馈均衡器对系统传输损伤的补偿性能.仿真结果表明,对于单信道40 Gbit/s NRZ系统,在同时考虑色散和自相位调制情况下,自适应判决反馈均衡器的引入可以使系统色散容限(1 dB眼图张开度代价)得到明显改善.在信号丢失率为10-3条件下,PMD容限由补偿前的0.17/单位比特周期,可提高到补偿后的0.22/单位比特周期.     

1T1R结构RRAM的故障可测性设计

阻变随机存储器(RRAM)中存在的故障严重影响产品的可靠性和良率.采用精确高效的测试方法能有效缩短工艺优化周期,降低测试成本.基于SMIC 28 nm工艺平台,完成了1T1R结构的1 Mbit RRAM模块的流片.详细分析了测试中的故障响应情况,并定义了一种故障识别表达式.在March算法的基础上,提出针对RRAM故障的有效测试算法,同时设计了可以定位故障的内建自测试(BIST)电路.仿真结果表明,该测试方案具有占用引脚较少、测试周期较短、故障定位准确、故障覆盖率高的优势.     

联合速率控制与功率分配的多信道无线网络跨层优化

本文基于凸优化方法,以提升网络效用与降低网络总功耗为目标,针对多无线多信道(Multi-radio Multi-channel)的多跳无线网络提出了一种联合速率控制与功率分配的跨层优化模型,并利用对偶分解方法设计了优化模型对应的分布式算法,证明了该分布式算法收敛性.该算法通过改变本征权的取值能够在网络效用与网络功耗之间取得折衷,并能根据速率要求动态调整各条链路的注入速率与发射功率使得网络达到效用与功耗的联合最优.通过仿真实验验证了该分布式算法可有效的调节网络效用与总功耗之间的平衡.     

Improved layered MIMO detection algorithm with near-optimal performance

A new layered symbol detection algorithm for multiple-input multiple-output systems is presented. In this scheme, the layers are divided into two groups and detected differently. For the layer with the smallest post-detection signal-to-noise ratio, an exhaustive search is performed over the signal constellation; for the remaining layers the conventional iterative vertical Bell laboratories layered space-time (V-BLAST) technique is utilised. The proposed algorithm also uses a different symbol detection ordering from that recommended in the original V-BLAST algorithm. Simulation results show that the error rate performance of the proposed detection algorithm approaches closely that of an optimal maximum likelihood detector with no reduction in the symbol detection throughput, while the computational complexity is less than |Q| times that of V-BLAST, where |Q| is the cardinality of signal constellation Q.     

Complementary sequences for ISI channel estimation

A merit factor based on the sequence autocorrelation function, whose minimization leads to the reduction in the Cramer-Rao lower bound (CRLB) for the variance of “two-sided” intersymbol interference (ISI) channel estimation is introduced. Pairs of binary pilot symbol sequences (a preamble and a postamble) for channel estimation are jointly designed to minimize this merit factor. Given that the number of channel taps is L and the length of a pilot symbol sequence is (N+L-1), where N⩾L, we distinguish between the case when N is even and the case when it is odd. For even N, we show that complementary sequences not only minimize the merit factor, but also the CRLB. For a subset of odd N we construct almost-complementary periodic sequence pairs that minimize the merit factor. The optimal pilot symbol block signaling requires alternating between two (in most cases) different binary sequences that form the merit-minimizing pair     

Joint power allocation and multi-relay selection scheme based on system outage probability

An amplify-and-forward （AF） based multi-relay network is studied. In order to minimize the system outage probability with a required transmission rate, a joint power allocation （PA） and multi-relay selection scheme is proposed under both total and individual power constraints （TIPC）. In the proposed scheme, the idea of ordering is adopted to avoid exhaustive search without losing much system performance. Besides the channel quantity, the ordering algorithm proposed in this article also takes relays＇ maximal output ability into consideration, which is usually ignored in traditional relay ordering algorithms. In addition, simple power reallocation method is provided to avoid repetitive PA operation during the process of searching all possible relay subsets. By Adopting the idea of ordering and using the proposed power reallocation method lead to remarkable decrease of the computation complexity, making the scheme easier and more feasible to implement in practical communication scenarios. Simulations show that the proposed multi-relay selection scheme provides similar performance compared to the optimal scheme with optimal PA and exhaustive search （OPAES） but with much lower complexity.     

Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization

Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.     

Average waiting time assignment. II. The integrated servicesnetwork case

For pt.I see ibid., vol.38, p.2049-51 (Nov. 1990). Priority scheduling as a means of selectively controlling the average delay of the users in a virtual circuit integrated services network is investigated. Specifically, quantifying the end-to-end delay preferences of the users on an individual basis through associated delay cost functions, the selection of the scheduling strategies on the links of the network is formulated as a convex optimization problem whose objective consists of minimizing the overall delay cost. A set of optimality conditions is given for this problem, and two distributed algorithms for solving it are constructed. The first algorithm always converges to an optimal solution, while the second algorithm is approximate. However, the second algorithm requires less coordination than the first, and by appropriately selecting the parameters the solution can be brought as close to optimality as desired. With simple modifications, the algorithms also solve the problem of selecting the scheduling strategies on the links so as to minimize the lexicographic ordering of the cost vector     

(s,Q) Spare Parts Provisioning Strategy for Periodically Replaced Systems

A joint preventive maintenance and spare parts provisioning strategy is suggested for a failure prone system. Replacements are carried-out at failure, if spare parts are available, and at spare parts replenishment delivery instants. Spare parts are provisioned according to an (s, Q) control policy. The ordering parameters, and preventive maintenance interval are derived from a mathematical model which aims at maximizing the system's availability under a budget constraint. The model takes into account the system lifetime distribution, the preventive and corrective maintenance costs and durations, as well as the total spare parts inventory management cost. Unlike classical inventory management models, the s-expected total cost is derived using the system lifetime distribution. Because each demand for spare parts is triggered by failure, the probabilities of shortage, and surplus will be evaluated based on the system failure distribution rather than the demand distribution during the lead-time. Numerical results have been obtained for an illustrative example.     

基于遗传算法的TBDD排序方法

带时间参数的二叉判决图（ＴＢＤＤ）在电路的时滞故障测试中有着重要的应用价值，但其变量排序是用常规方法无法解决的一个优化问题。本文提出一种基于遗传算法的ＴＢＤＤ排序算法。用快速衡量值和ＴＢＤＤ节点数来计算个体的适应度。针对变量排序的特定问题，提出一种模板保序交叉方法。采用知适应的变异概率计算方法，并提出一个适合于ＴＢＤＤ排序问题的变异算法。实验结果表明较好地解决了ＴＢＤＤ的排序问题。     

Max–min utility fair flow management for networks with route diversity

A regional central manager is employed to set aside, for the regional (or back-bone) network that it manages, for each flow class, communications capacity resources for a specific future time horizon. In the context of such a traffic management operation, a longer temporal scale is involved in controlling the admission and distribution of flows across the network. For management scal-ability purposes, flows are aggregated into flow classes. Furthermore, we consider a network operation under which multiple simultaneously activated routes are employed, across possibly distinct segments, to distribute traffic between identified source–destination pairs. We aim to ensure that the utility assigned to each class is as high as feasibly possible while striving to raise the utility gained by all classes in a max–min fair manner. In doing so, we incorporate the communications capacity constraints that are imposed by the underlying hybrid of directional and/or multiple-access wireline and wireless communications media employed across the network system. We develop and present in this paper an optimal algorithm for solving such a traffic management problem. It yields multi-utility-based max–min fair distributions of flow rates, per each class, across the specified multitude of simultaneously activated multi-segment routes. To guarantee that admitted flows are granted their desired capacity resources (and targeted corresponding utility levels), the selection of optimal flow distributions across the network routes is combined with the use of a flow admission control scheme that serves to optimally limit the aggregate rate of flows admitted for each flow class. As illustrative examples, we demonstrate the effectiveness of our solution in comparing its performance with that obtained under the use of a traffic regulation scheme that is not overlaid with a traffic management mechanism that serves to set aside resources for the support of flow classes. We also illustrate the use of our optimal algorithm for determining the optimal placement of unmanned aerial vehicle platforms that serve to supplement a terrestrial transport segment with a space-based one. Copyright © 2010 John Wiley & Sons, Ltd.     

Small-Signal Second-Harmonic Generation by a Nonlinear Transmission Line (Short Paper)

Second-harmonic generation (SHG) by a relatively low-loss transmission line having a capacitive nonlinearity is treated with an extended small-signal analysis. This simple theory brings out the relevance of "phase matching" the fundamental- and second-harmonic waves and of reducing losses in order to optimize SHG. It is shown that maximum SHG will occur when the line is short compared with its "coherence length" and has radian electrical length equal to twice its "transmission Q" at the second-harmonic frequency. The product of a line's "transmission Q" and its "nonlinearity factor" should be maximized to obtain maximum efficiency and is, therefore, believed to be a useful figure of merit for comparing the SHG potential of different transmission-line implementations.     

Expert systems tools for hubble space telescope observation scheduling

Construction of an efficient yearlong observing program for the Hubble Space Telescope (HST) requires the ordering of tens of thousands of proposer-specified exposures on a timeline while satisfying numerous coupled constraints. Although manually optimized planning can be performed for short time periods, routine operations will clearly require that most of the planning be done by software. This paper discusses the utility of expert systems techniques for HST planning and scheduling and describes a plan for development of expert system tools which will augment the existing ground system. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool (ART) running on a Texas Instruments Explorer Lisp workstation.