无线传感器网络中能量有效分簇路由算法

由于无线传感器节点的电源能量有限,提出了一种能量有效分簇路由算法(EECRA).该算法是基于最小能量的数据转发并运用于簇内路由中,簇头由基站根据节点的剩余能量和簇头之间的距离来选定,为了减小簇头节点的能量开销,簇头之间采用了多跳中继的方式将采集的数据发送到基站.仿真结果证明:该算法与LEACH协议相比,不仅提高了网络寿命,同时节点的能耗均衡性、网络扩展性和可靠性都大大的提高.     

混合车型需求响应公交服务定制问题研究

针对现存需求响应公交服务中服务质量与服务效率的矛盾,本文提出一种使用混合车型的需求响应服务定制方法.首先采用基于k-means的算法,获得具有时空特性的服务单元.在此基础上,将载运车辆的分配与路径规划问题,视为一个带时间窗的取送问题,通过Dantzig-Wolfe分解,以最小化走行距离和使用车辆数为目标,构建需求响应公交服务定制等价分解模型.在MapReduce框架下,设计了分布式列生成算法,提出了解的可行性保障机制.最后,求解以北京市为背景的案例,验证了模型和方法的可行性和正确性.     

Improved Kernel Possibilistic Fuzzy Clustering Algorithm Based on Invasive Weed Optimization

Fuzzy c-means(FCM) clustering algorithm is sensitive to noise points and outlier data, and the possibilistic fuzzy c-means(PFCM) clustering algorithm overcomes the problem well, but PFCM clustering algorithm has some problems: it is still sensitive to initial clustering centers and the clustering results are not good when the tested datasets with noise are very unequal. An improved kernel possibilistic fuzzy c-means algorithm based on invasive weed optimization(IWO-KPFCM) is proposed in this paper. This algorithm first uses invasive weed optimization(IWO) algorithm to seek the optimal solution as the initial clustering centers, and introduces kernel method to make the input data from the sample space map into the high-dimensional feature space. Then, the sample variance is introduced in the objection function to measure the compact degree of data. Finally, the improved algorithm is used to cluster data. The simulation results of the University of California-Irvine(UCI) data sets and artificial data sets show that the proposed algorithm has stronger ability to resist noise, higher cluster accuracy and faster convergence speed than the PFCM algorithm.     

列车通信以太网周期数据时态约束调度方法

针对工业以太网调度方法以报文截止期为唯一约束的局限,提出了一种基于时态约束的列车通信网络周期数据调度表生成方法.首先基于时间触发机制改造列车以太网的通信与消息模型;其次利用网络设备通信参数与数据报文参数,提出周期数据通信的时态约束有向图量化模型;最后设计了基于可满足性模理论的调度表生成算法,求解单播及广播业务的周期数据调度表以验证算法有效性,并在实际列车通信网络的拓扑条件下进行调度性能测试及分析.实验结果表明:该调度算法能够解决部分传统算法不能调度的通信任务,满足更细化的周期数据调度需求并提升调度灵活性;调度性能测试中最大链路负载超过80%,可调度周期数据业务量达到1 000项.      

基于能量与功率控制的TopDisc拓扑算法研究

拓扑控制是无线传感器网络的一个重要研究方向,选择良好的拓扑控制机制,能够提高网络通信效率并延长网络的生命周期。在TopDisc算法的基础上,提出了一种基于能量与功率控制的拓扑控制算法,在能量的引导下,通过调整节点的发射功率,生成更适合的网络拓扑结构。仿真实验结果表明改进的算法形成的簇的交叠更少,网络的生存时间更长。     

Research on Improved Low-Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Networks

In wireless sensor networks (WSNs), due to the limited battery power of the sensor nodes, the communication energy consumption is the main factor to affect the lifetime of the networks. A reasonable design of the communication protocol can effectively reduce the energy consumption of the network system. Based on low-energy adaptive clustering hierarchy (LEACH), an improved LEACH protocol in WSNs is proposed. In order to optimize the cluster head (CH) election in the cluster setup phase, the improved LEACH takes into account a number of factors, including energy consumption of communication between nodes, remaining energy of the nodes, and the distance between nodes and base station (BS). In the steady phase, one-hop routing and multiple-hop routing are combined to transmit data between CHs to improve energy efficiency. The forward CH is selected as relay node according to the values of path cost. The simulation results show that the proposed algorithm performs better in balancing network energy consumption, and it can effectively improve the data transmission efficiency and prolong the network lifetime, as compared with LEACH, LEACH-C (LEACH-centralized) and NDAPSO-C (an adaptive clustering protocol based on improved particle swarm optimization) algorithms.     

Optimization of CMOS repeater driven interconnect RC line using genetic algorithm

In this work, optimization of complementary metal oxide semiconductor (CMOS) repeater driven interconnect resistive-capacitive (RC) line is carried out using genetic algorithm (GA). This work is aimed at powerdelay- product (PDP) minimization of RC interconnect at 180 nm technology node. The algorithm simultaneously optimizes the values of supply voltage, number of repeaters and repeater width for delay and PDP minimization. The accuracy of results obtained is verified by simulations from Cadence virtuoso tool. For delay minimization, comparison of GA results with previous results of the literature shows an improvement of 44.4% in the value of the optimal number of repeaters required. This improvement is obtained by increasing the repeater size, which also increases power dissipation, so a tradeoff has also been achieved in terms of PDP minimization. The comparison of PDP results obtained in this work, with the results at 70, 100, and 130 nm technologies from literature shows improvement in optimal number of repeaters required. The results of algorithm and simulations are in good agreement and demonstrate the validity of proposed algorithm.     

A Distributed Power Allocation Scheme in Green Cognitive Radio Ad Hoc Networks

For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network topology, it needs to consider how to optimize the throughput and power consuming, avoid the interference to primary users(PUs) and other SUs, and pay attention to the convergence and fairness of the algorithm. In this study, this problem is modeled as a constraint optimization problem. Each SU would adjust its power and corresponding strategy with the goal of maximizing its throughput. By studying the interactions between SUs in power allocation and strategy selection, we introduce best-response dynamics game theory and prove the existence of Nash equilibrium(NE) point for performance analysis. We further design a fully distributed algorithm to make the SUs formulate their strategy based on their utility functions, the strategy and number of neighbors in local area. Compared with the water-filling(WF) algorithm, the proposed scheme can significantly increase convergent speed and average throughput, and decrease the power consuming of SUs.     

均匀设计和遗传操作并行的遗传算法

针对简单的遗传算法稳定性较差，容易发生早熟收敛的不足之处，提出了将均匀设计和遗传操作相结合的遗传算法，通过编码在问题的解空间和算法的搜索空间之间建立一个映射，对其进行交叉操作，变异操作和均匀设计操作，用典型的测试函数进行测试，证明了该算法是可行的，与单纯遗传算法相比，计算精度和收敛速度更高。     

基于交叉熵算法的电动车辆复合电源参数优化

为了提升电动汽车动力性能、降低车辆成本，以复合电源成本和车辆电耗最小为目标，通过交叉熵（cross- entropy，CE）算法对车载复合电源的参数优化进行了研究. 首先，以某款纯电动汽车为研究对象，根据能量与功率性能指标确定锂离子电池和超级电容的容量范围；其次，选取复合电源成本和车辆电耗建立多目标优化函数，并在ADVISOR环境中搭建车辆仿真模型；接着，采用CE算法，通过种群的不断迭代，更新高斯概率密度函数的均值和方差，找到复合电源参数的Pareto最优解集；最后，从最优Pareto解集中选取典型的匹配参数，分析复合电源成本、车辆电耗和整车性能. 研究结果表明:在满足基本约束的前提下，得到了由100个解组成的Pareto最优解集. 与第二代非劣排序遗传算法（non-dominated sorting genetic algorithm-Ⅱ，NSGA-Ⅱ）比较，CE算法有更好的收敛性与分布性；复合电源成本平均降低了9.49%，车辆电耗平均降低了22.81%； 此外，城市道路循环工况（urban dynamometer driving schedule，UDDS）下车速误差最大值降低16.15%，整车动力性也有显著提升，百公里加速时间缩短7.81%，最高车速提升1.98%.      

基于能效的D2D通信系统中资源复用策略研究

针对D2D通信(device-to-device communication)与传统蜂窝通信共存下的能效资源复用问题,联合考虑蜂窝用户和D2D用户对的QoS约束,结合电路消耗功率,提出一种基于能效的D2D用户对与蜂窝用户最优匹配的资源复用和功率分配策略,分析了D2D用户对复用蜂窝用户资源的最优功率的存在性,并用分式规划理论求解了该最优功率的闭合表达式.仿真结果表明,相比已有算法,所提的能效资源复用策略的D2D用户的总能效最优,并且该总能效在低QoS要求下相比最大化和速率算法提高36.25%,高QoS要求下略高于基于节能的功率分配算法,同时还具有1.7~3 Mbit/s的和速率.      

��ͨ��Ϣ�ɼ���WSN�ִ��㷨�о�

无线传感网是采集实时交通信息的重要工具.因其节点能量有限,必须设计高能效的分簇路由算法以延长网络周期.本文通过建立一种智能交通中无线传感器网络的应用模型,根据其特点和要求分析LEACH协议的优缺点并提出一种能量负载均衡的分簇算法.该算法对LEACH协议当中的簇首机制进行改进,综合考虑候选节点的剩余能量和簇首节点的分布位置;建立簇间多跳路由机制以避免单跳通信的大能量消耗;创造一种簇重构方法,避免过于频繁的簇重构引起的不必要能量消耗.仿真结果表明,能量均衡算法可有效平衡节点能量消耗分布,延长网络生命周期,可很好的应用于基于WSN的ITS当中.     

基于拓扑判断的海量GPS数据延时地图匹配算法

由于浮动车数据采集中存在GPS数据周期过长、拓扑关联性较差、数据量大的特点,传统的车载端地图匹配算法难以直接应用,针对车辆无法初次匹配的情况,设计了一种可根据路网拓扑关联性进行判断的延时地图匹配算法.实际数据验证表明,该算法在保证数据完整性和有效性的基础上,可以实时、准确地进行地图匹配,尤其是车辆位于复杂交叉口及高架桥附近区域时车辆真实行驶道路的确定.      

����ר�߳�վ�����������Ż�����

车站的拓扑结构限定了作业线的用途,依据车站的接发车作业要求,分类使用作业线可以有效地减少作业干扰,提高车站作业效率.根据车站的拓扑结构和接发车任务,把到发线的优化目标分解为满足到发线运用规则、利于乘降作业、设备均衡使用等目标,并建立了优化模型.运用遗传算法对模型求解.提出了诱导变异的概念,通过诱导变异避免变异产生病态个体,保证群体的健康.最后通过实例验证了模型和算法的合理性.结果表明,在能力允许的条件下,算法的效率较高并能够取得较优解,满足客运专线车站作业的要求.     

SoC的可靠性和低功耗协同优化

针对SoC的高可靠性和低功耗的设计要求,分析了动态电压与频率调节技术对系统功耗、温度和软错误率的影响,构建了SoC的可靠性和功耗的协同优化设计模型,提出了可靠性和低功耗协同设计的新方法,并通过考虑可靠性的动态电压与频率调节调度算法进行了仿真,验证了算法的有效性和可行性.结果表明,在可靠性降低5%的情况下,可节省约15.99%的功耗.     

互联网定制公交的网络调度模型及其求解算法

针对互联网定制公交服务模式中存在的路线规划不合理、缺乏成熟的通用模型等问题,本文首先采用K-mean算法对居民的实时出行需求进行聚类,在此基础上构建了面向互联网定制公交,以最大需求服务率和最小费用为双层目标,以最大载客量和乘客时间阈值等因素为约束条件的动态网络调度模型,进而针对模型的快速求解设计了基于Hadoop平台的并行蚁群算法.以广州市为例,对模型与算法的有效性、实时性进行检验,结果表明,所提出模型和算法可应用于实际互联网定制公交业务中,对推进"互联网+交通运输"具有积极的意义.     

考虑船舶封存与压港的电煤船舶调度优化模型

针对中国电煤水运系统的实际特点, 综合考虑了船舶封存与港口拥堵(压港)因素, 建立了混合整数规划优化模型, 对电煤船舶调度方案进行优化; 基于运输需求的硬时间窗、卸货港船舶排队等待时间与水路-铁路运输协同三因素之间的互动关系, 以运输系统总成本最小为目标, 协同优化水、铁电煤运输的货运分担率、水路运输任务指派和相应的船舶调度与封存/启用方案; 基于改进列生成算法, 提出了一种可精确求解实际规模电煤船舶调度问题的列生成算法, 利用Gurobi求解列生成的主模型, 使用动态规划标号法求解列生成的子模型; 利用中国南部某火力发电集团的实际数据, 对提出的算法进行了算例分析。计算结果表明: 在中等规模的算例中, 使用提出的改进算法获得最优解仅需73.61 s, 相比于使用基于运输任务运量排序的启发式求解方法(PHA), 求解效率提高了18.1%;在较大规模的算例中, 使用提出算法的计算时间仅为222.02 s, 同比PHA, 计算效率提高了19.1%;通过求解一个实际的调度问题可以发现, 利用提出的优化模型和算法能有效缩短船舶在卸货港的等待时长与船舶处于启用状态的时长, 使运输总成本下降17.13%, 实现了电煤稳定运输, 提升了企业运营效率, 降低了运营成本。      

Power-Aware Anycast Routing in Wireless Sensor Network Exploiting Small World Effect

By considering energy-efficient anycast routing in wireless sensor network (WSN), and combining small world characteristics of WSN with the properties of the ant algorithm, a power-aware anycast routing algorithm (SWPAR) with multi-sink nodes is proposed and evaluated. By SWPAR, the optimal sink node is found and the problem of routing path is effectively solved. Simulation results show that compared with the sink-based anycast routing protocol (SARP) and the hierarchy-based anycast routing protocol (HARP), the proposed algorithm improves network lifetime and reduces power consumption.     

基于刚分簇与鸡群优化的深井无线传感网络定位算法

针对矿井环境因素对无线传感器网络定位的制约,提出一种基于刚性分簇与鸡群优化的无线传感器网络定位算法(RCCSO). 首先,以传感网络中均匀分布的锚点为簇头,基于刚性图理论提出分簇算法对整个网络进行分簇并保证每个簇都是全局刚性的;其次,利用鸡群算法对簇内进行相对定位,求得簇内最优相对位置解集;再次,不同簇以锚点为旋转中心旋转不同角度,并利用鸡群算法求出旋转角度的最优解集,进而求得全局节点最优位置;最后,仿真结果显示,与多维标度MDS-MAP算法及自适应局部区域循环搜索DALSA相比,所提算法在精度上有较明显的提高.      

Development of a wireless capsule endoscope system based on field programmable gate array

A new modular and programmable wireless capsule endoscope is presented in this paper. The capsule system consumes low power and has small physical size. A new image compression algorithm is presented in this paper to reduce power consumption and silicon area. The compression algorithm includes color space transform, uniform quantization, sub-sampling, differential pulse code modulation (DPCM) and Golomb-Rice code. The algorithm is tested in a field programmable gate array (FPGA) development board, and the final result achieves 80% compression rate at 40 dB peak signal to noise ratio (PSNR). The algorithm has high image compression efficiency and low power consumption, compared to other existing works. The system is composed of the following three parts: image capsule endoscope, portable wireless receiver and host computer software. The software and hardware design of the three parts are disscussed in details.