Utility function based fair data scheduling algorithm for OFDM wireless network

A system model is formulated as the maximization of a total utility function to achieve fair downlink data scheduling in multiuser orthogonal frequency division multiplexing （OFDM） wireless networks. A dynamic subcarrier allocation algorithm （DSAA） is proposed, to optimize the system model. The subcarrier allocation decision is made by the proposed DSAA according to the maximum value of total utility function with respect to the queue mean waiting time. Simulation results demonstrate that compared to the conventional algorithms, the proposed algorithm has better delay performance and can provide fairness under different loads by using different utility functions.

A utility-optimal backoff algorithm for wireless sensor networks

A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput.

Utility-optimization dynamic subcarrier allocation algorithm for SC-FDMA systems

Two utility-optimization dynamic subcarrier allocation(DSA) algorithms are designed for single carrier frequency division multiple access system(SC-FDMA).The two proposed algorithms aim to support diverse transmission capacity requirements in wireless networks,which consider both the channel state information(CSI) and the capacity requirements of each user by setting appropriate utility functions.Simulation results show that with considerable lower computational complexity,the first utility-optimization algorithm can meet the system capacity requirements of each user effectively.However,the rate-sum capacity performance is poor.Furthermore,the second proposed utility-optimization algorithm can contribute a better trade-off between system rate-sum capacity requirement and the capacity requirements of each user by introducing the signal to noise ratio(SNR) information to the utility function based on the first utility-optimization algorithm,which can improve the user requirements processing capability as well as achieve a better sum-rate capacity.

Dynamic bandwidth allocation algorithm for full-band utilization

To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized （DFBU） allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth （up to full-bandwidth） while the performance of fairness and QoS requirement is still guaranteed.

Agricultural Water Resources Utilization and Management under Agricultural Safety Aim Based on Fuzzy Neural Network Algorithm

[Objectives]To explore the agricultural water resources utilization and management under the agricultural safety aim.[Methods]Fuzzy neural network algorithm was adopted.The evaluation model of agricultural water resources utilization and management carrying capacity based on quantitative system was established.[Results]With the remarkable improvement of China's national income,great progress has been made in China's agricultural development.However,in the process of agricultural safety production,the problem of sustainable development has not been noticed,the problem of water resources exceeding the limit bearing capacity frequently occurs.[Conclusions]It is of great significance to effectively solve the problem of water resources utilization and management.In the feasibility test for the algorithm,further tests on various indicators show that the research is feasible.

DYNAMIC BANDWIDTH ALLOCATION ALGORITHM UTILIZING FULL BAND

A kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm is introduced. This algorithm allows a single link to use bandwidth far beyond its fair share bandwidth in a multi-service packet transporting system. Three important parameters as the bound on maximum and minimum bandwidth, the maximum packet delay and the minimum band width utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system to use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.

PHUI-GA: GPU-based efficiency evolutionary algorithm for mining high utility itemsets

Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search space.EAs have good running and mining performance,but they still require huge computational resource and may miss many HUIs.Due to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded processors.Experiments show that the mining performance of PHUI-GA outperforms the existing EAs.When mining 90%HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.

基于电气自动化的灌溉水电双控系统设计

针对我国灌溉系统水资源利用率较低的问题,基于电气自动化对灌溉水电双控系统进行了设计。灌溉水电双控系统主要组成包括控制模块、信息采集模块、收费管理模块、执行模块和通信模块。为了实现节水灌溉,提升水利用率,在管理方面对控制系统软件进行设计,在技术方面对控制系统算法进行设计。为了验证灌溉系统的性能,对系统进行了数据计量准确性试验和节水灌溉运行试验。试验结果表明:系统可以准确地测量用电量和用水量,且可自动启动节水灌溉。

考虑乘客感知效用的出租车停靠站选址模型

为了解决城市出租车停靠站布局的合理性问题,对出租车GPS数据进行处理并将乘客出行需求点进行聚类,得到出租车停靠站备选点以及乘客出行需求点。基于出租车停靠站服务能力和距离影响因素,结合竞争选址理论构建出租车停靠站对乘客的感知效用函数。在此基础上,以覆盖乘客出行需求量最大为目标,建立考虑乘客感知效用的出租车停靠站选址模型,以确定出租车停靠站的最佳位置。根据问题特征设计近似算法A进行求解,在求解大规模算例时,与遗传算法、萤火虫算法相比,近似算法求解精度提高0.91%,求解时间降低约97%。以西安市莲湖区局部区域为例进行实例分析,算法求解近似比为1.64,说明算法的实际使用效果较好。

考虑区域资源利用均衡的电动公交充电站选址及充电路径问题

在新基建助推区域平衡发展和低碳双重背景下,研究电动公交充电站选址及充电路径问题,以经济效益最大化和区域资源利用均衡为目标,考虑公交司机可能充电时机以及充电需求、运营时间、利用率等约束条件建立两阶段多目标决策模型,设计多重嵌套式遗传算法求解模型,并应用于算例检验模型可行性。结果表明:仅考虑经济效益目标会产生充电“拥挤”、路途过长等弊端,而本文模型能有效缩小区域间公交充电效率差异,提高全局资源利用均衡性;通过降低充电站容量可提高充电站利用率与经济效益,但区域资源利用均衡性会减弱,且充电站容量对公交充电路途所耗费时间的作用较为敏感;适当增加区域资源利用均衡目标的权重更有利于提高总体优化效果。研究结果可为公交充电站选址和路径规划提供决策支持。

完全预约模式下船闸通航调度方法分析

针对现有部分船闸通航效率不高,通航拥堵严重等问题,以完全预约模式下船闸通航调度方法为研究对象,考虑闸室有效面积利用率最大和平均预约延误时间最小,在BL算法的基础上,建立了基于人工蜂群算法的船闸通航调度模型。选取三峡双线五级船闸的过闸船舶数据,通过与原始人工编排、BL算法编排结果进行比较,发现人工蜂群算法性能稳定,能显著提高闸室面积利用率,且平均利用率大于80%。此外,在平均预约延误时间方面有明显的降低效果。

基于全局寻优的旅游路线自动调度系统设计

由于系统调度旅游路径时,部分景点游客数量较多且排队等待时间较长,为缩短行走和排队等待时间等问题,对基于全局寻优的旅游路线自动化调度进行系统设计。选取嵌入式中央处理器作为核心器件,采集游客行走速度和位置信息;分析游客偏好、景点拥挤程度与旅游感受的关系,结合游客感受和旅游成本,计算游客旅游效用值,采用蚁群算法将效用值作为蚂蚁信息素强度,全局寻优景区内的最佳旅游路线。实验结果表明,采用该方法的设计系统平均行走时间为46.7 min,平均排队等待时间为28.1 min,设计系统调度路线下的游客行走时间、排队等待时间最短,减少了游客时间消耗。

基于最小剩余时间算法与SR-IOV技术的GPU资源优化调度方案

为了优化GPU资源利用率,文章提出了一种新型的GPU资源调度方案。该方案结合了最小剩余时间算法与SR-IOV(SingleRootI/OVirtualization)技术,可优化多用户、多任务环境下的GPU资源利用率和系统性能。传统的GPU调度方法往往面临资源利用不足、任务等待时间长和系统吞吐量受限等问题。为了应对这些挑战,该方案通过动态分析任务的剩余执行时间,利用SR-IOV技术实现了GPU资源的细粒度隔离与共享,可为更高效的资源分配和任务调度提供支持。实验结果表明,相较于传统的无调度、容器调度和常见机器学习调度方案,该方案在均值准确率、GPU利用率、系统吞吐量和任务执行时间等方面均具有一定的优势,可为多用户多任务场景下的GPU资源管理提供有益的参考。

HHUIM:一种新的启发式高效用项集挖掘方法

针对基于启发式的高效用项集挖掘算法在挖掘过程中可能丢失大量项集的问题,提出一种新的启发式高效用项集挖掘算法HHUIM。HHUIM利用哈里斯鹰优化算法进行种群更新,能够有效减少项集丢失。提出并设计了鹰的替换策略,解决了搜索空间较大的问题,降低了适应度函数值低于最小效用阈值的鹰的数量。此外,提出存储回溯策略,可有效防止算法因收敛过快陷入局部最优。大量的实验表明,所提算法优于目前最先进的启发式高效用项集挖掘算法。

基于差分进化算法的旧采空区水分质利用优化配置

大部分矿井水污染程度低,稍加处理即可供饮用、工业、农业、生态等使用。焦作煤田吴村矿旧采空区水可供水量为718 m^(3)/h,矿区周围饮用、电厂、灌溉、养殖、生态等用户需水量为1073.74 m^(3)/h,旧采空区水仅能满足66.87%的用水需求;旧采空区水需处理达标后才能供给用户,不同用户的水处理工艺和费用差异较大,依据水质优化配置旧采空区水量具有重要意义。目的为了实现矿井排水综合利用效益最大化,方法以焦作煤田吴村矿旧采空区水为研究对象,在计算其供水量和分析水质基础上,结合矿区周围饮用、电厂、灌溉、养殖、生态需水量及水质要求,构建718 m^(3)/h旧采空区水分质利用优化配置数学模型,并利用差分进化算法求解。结果结果表明:灌溉期分配饮用水6.00 m^(3)/h、电厂用水334.95 m^(3)/h、灌溉用水353.89 m^(3)/h、养殖用水19.76 m^(3)/h、生态用水3.40 m^(3)/h;非灌溉期分配饮用水6.00 m^(3)/h、电厂用水688.84 m^(3)/h、灌溉用水0 m^(3)/h、养殖用水19.76 m^(3)/h、生态用水3.40 m^(3)/h时,旧采空区水分质利用年收益最大。结论研究结果可为类似矿井旧采空区水和矿井排水资源化利用提供借鉴。

多块排样方式的二维板材下料优化模型与算法

针对矩形件二维板材剪切下料问题,提出一种多块排样方式的二维板材下料优化模型与求解算法。为了均衡考虑排样方式的计算复杂度和板材利用率,将多块排样方式的块数定为八块。通过3次一分为二剪切操作将板材分割成八个矩形块,并将每个块剪切成方向相同的同种矩形件。构造八块排样的优化模型及算法是按照排样价值最大原则来确定所有可能尺寸的块中矩形件的最优布局和板材的最优八块划分。提出的列生成算法迭代调用上述八块排样算法生成一系列下料方案,选择耗费板材最少的一个下料方案作为最终解。通过采用文献基准例题和实际生产实例验证了本文算法,实验结果表明:八块排样算法的排样价值高于3种文献排样算法,并且,八块排样方式的下料算法板材利用率高于已有文献给出的下料算法。本文给出算法计算时间可满足实际应用需要。

A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data Centers

As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be optimized.Although many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with it.Therefore,how to improve the data center power capacity utilization while ensuring power supply security has become an important issue.To solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system.HGAACS uses historical power data of each server to find a better placement solution by population iteration.HGAACS possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement algorithms.The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.

区间水优先的水库群引供水调度规则研究

【目的】随着跨流域调水工程不断地发展与完善,没有调节能力的闸坝逐渐与水库共同参与到调度中来,对需要考虑多流域丰枯特性和多水库调节能力的调度规则制订提出了更大的挑战。【方法】为此,提出在调水中相对于水库优先利用区间水的原则,以此构建系统总弃水量最小的调度模型,利用改进的遗传算法求解得到调度规则。并且,以石湖-龙湾-碧流河水库与黑鱼汀闸坝联合的引洋入连引调水工程作为研究实例进行对比。【结果】结果显示,相比于常规调度,优先利用区间水的调度规则方案规避了系统深度破坏,满足95%保证率的城市供水需求,多年平均引水量增加了0.79亿m^(3),系统年均弃水量减少了2.1亿m^(3)。【结论】该研究方法较好地提高了区间水的利用率及系统的用水效率,可为有闸坝参与的跨流域调水系统的调度提供科学参考和技术支撑。

基于遗传蚁群算法的无源光通信网络重构研究

无源光通信网络的资源利用率直接关系到该网络的通信服务质量。在此背景下,为实现高质量通信,提出基于遗传蚁群算法的无源光通信网络重构方法。该研究在8条假设条件下,以资源利用率最大化为目标,在7个约束条件下,利用遗传蚁群算法求取满足目标函数的最优解,得到无源光通信网络重构方案。结果表明:设计方法应用下的无源光通信网络资源利用率较高,最高为96%,说明设计方法能以最小的资源消耗实现通信传输,具有一定的应用价值。

半参数双重Tweedie复合泊松回归模型的贝叶斯分析

为了分析健康保险行业中出现的半连续卫生保健费用数据,本文提出一类半参数双重Tweedie复合泊松回归模型.在分析中,首先采用修正鞍点逼近的数值方法去近似Tweedie复合泊松分布的密度函数;其次,利用Gibbs抽样技术和Metropolis-Hastings(MH)算法的混合算法获得了模型参数的联合贝叶斯估计;最后,给出了几个模拟研究以及把这些方法用来分析兰德健康保险实验中的卫生保健费用数据.