A new load balancing scheme on heterogeneous database cluster

In heterogeneous database cluster, the performance of load balancing is closely related to the computing capabilities of heterogeneous nodes and the different types of workloads. Thus, a method is introduced to evaluate the load status of nodes by the weighted load values with consideration of both the utilization of different resources and the workload types in a load balancer and an efficient and dynamic load balancing scheme is proposed for OLTP(online transaction processing) workloads to maximize the utilization of distributed resources and achieve better performance, which need not collect the feedback of load information from the lower nodes and effectively keeps from the data skew. The simulation results for OLTP services gained by TPC-C tool show that the dynamic weighted balancing policy leads to sub-linear throughput speedup and keeps the heterogeneous cluster well balanced.     

WebGIS集群环境下Client主动式负载均衡策略

针对现有WebGIS集群环境下负载均衡调度策略的特点和弊端进行分析,提出了WebGIS集群环境下Client主动式负载均衡策略,重点研究了无中心(负载均衡调度中心)的WebGIS集群体系结构和Client主动式任务均衡分解方法,最终实现WebGIS集群环境下各服务节点间的负载均衡,解决了传统WebGIS模型中存在的负载均衡调度中心节点请求转发性能瓶颈问题和请求响应延迟问题。最后,使用不同规模大小的并发访问用户进行实验,结果证明,与传统的WebGIS集群环境下负载均衡策略相比, Client主动式负载均衡策略能更有效地缩短服务的平均响应时间,提高WebGIS集群的并发处理能力,且并发访问用户量越大,效果越明显。     

网络GIS中最佳负载均衡的分布式缓存副本策略

云环境下的网络地理信息服务具有分布性和异构性,空间数据(瓦片)的访问请求具有高度聚集性和不均匀性。以最小化负载不均衡度为目标,提出了一种应用于异构的、分布式高速缓存集群系统的多副本策略。该策略针对瓦片访问请求存在不均衡性,最小化热点访问数据的通信权重值,最大化地利用分布式集群缓存能力生成副本;针对异构集群环境下服务器处理能力的不均衡性,根据服务器性能和瓦片副本的通信权重值,匹配各个服务器的缓存能力部署副本。实验证明,该策略避免服务器拥塞的同时,能充分利用有限的分布式集群缓存能力,实现较好的负载均衡和较高的资源利用率,并能获得良好的缓存命中和请求响应性能。     

用户访问驱动的空间数据存储组织策略

针对用户访问服务负载均衡的分布存储要求和磁盘连续读取的合并存储要求之间的矛盾，提出一种基于用户访问行为的综合考虑存储节点连续读取效率和网络负载均衡效率的空间数据存储组织方法（combined strategy of data placement and load balance，CSDL）。该方案根据用户访问行为，通过空间数据的访问相关性计算，将热点数据分布存储在不同的服务器上，以实现用户并发访问时的负载均衡；同时，通过对存储在相同服务器内数据的并发度计算，将并发度高的数据存储在连续的磁盘空间上，以实现磁盘存储服务的连续读取。CSDL方法试图同时从上层应用的负载均衡和底层磁盘效率两个方面对空间数据的存储进行分布组织，以提高地理信息系统服务效率。试验结果表明，该方案可有效提高45.2%~245.3%的系统平均请求响应时间，与此同时，分布式服务器节点的负载均衡度可提高约0.5%~440.9%，能满足大规模分布式环境的应用需求。     

空间数据服务效率优化策略

分析了空间数据服务的特点和现状,探讨了提高数据传输效率的技术途径、提出了基于Grid FTP集群的空间数据服务效率优化策略,设计了基于动态数据分块和服务性能加权的负载均衡算法并开展了相关实验.实验结果表明、提出的优化策略是可行、有效的,能够显著的改善大数据量空间数据集的传输效率.     

利用遗传算法的网络GIS集群服务器动态负载均衡算法

针对现有负载均衡方法的不足和网络GIS数据的特点,提出了一种基于遗传算法的网络GIS集群服务器动态负载均衡方法。该算法将基于服务器状态和基于内容的调度算法综合起来考虑,设计了相应的编码机制和遗传操作。实验结果表明,和常用的负载均衡算法相比,此算法能获得更小的服务请求响应时间,能更好地服务网络GIS系统。     

无人机影像应急并行处理负载均衡方法

基于应急条件下的计算机和网络资源,以实现无人机影像应急并行处理为目的,提出了一种简洁的负载均衡实现方法。采用了以进程为调度单元的主动式计算资源统计策略,辅以任务队列二级动态分配方法,实现了负载均衡。使用本方法在应急环境中建立简易的并行化集群处理系统,可以灵活、高效、鲁棒地利用可用的计算资源,大幅缩短无人机影像应急处理时间。为验证本文负载均衡方法的有效性,利用无人机机载定位定向系统记录的定位定向参数,结合已知数字高程数据,完成了无人机影像的初步正射纠正和拼图处理。实验结果表明,该方法实现简单、部署方便、扩展灵活、任务分配均衡,处理效率随着计算单元的增加而提高,可大幅提高应急条件下无人机应急影像图制作效率。     

pRPL 2.0: Improving the Parallel Raster Processing Library

This article presents an improved p arallel R aster P rocessing L ibrary – pRPL version 2.0. Since the release of version 1.0, a series of modifications has been made in pRPL to improve its usability, flexibility, and performance. While retaining some of the key features of pRPL, the new version has gained several new features: (1) a new DataManager class has been added for integrated data management, and to facilitate data decomposition, assignment mapping, data distribution, Transition execution, and load‐balancing; (2) a GDAL‐based raster data I/O mechanism has been added to support various geospatial raster data formats, and provide centralized and pseudo parallel I/O modes; and (3) a static load‐balancing mode and a dynamic load‐balancing mode using the task‐farming technique are provided. A parallel zonal statistics tool and a parallel Cellular Automata model were developed to demonstrate the usability and performance of pRPL 2.0. The experiments using the California datasets showed that the performance altered when different pRPL options (i.e. load‐balancing mode, I/O mode and writer mode) were used for different algorithms, datasets, and varying numbers of processes.     

PMODTRAN: a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission (MODTRAN) is a commercial remote sensing (RS) software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth's atmosphere and the radiation observed by a remote sensor. However, when very large RS datasets must be processed in simulation applications at a global scale, it is extremely time-consuming to operate MODTRAN on a modern workstation. Under this circumstance, the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task. This paper presents PMODTRAN, an implementation of a parallel task-scheduling algorithm based on MODTRAN. PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster. In addition, PMODTRAN can distribute tasks with different levels of granularity and has some extra features, such as dynamic load balancing and parameter checking.     

基于集群的陕西省电子地图网站负载均衡设计与实现

集群与负载均衡是大型在线网站解决网络瓶颈、提高网络灵活性和可靠性的一种策略。文章分析了集群与负载均衡的相关技术,结合陕西省电子地图网站提出了基于集群的地图网站负载均衡策略,并进行了试验。     

弹性伸缩控制技术及在地理国情普查中的应用

目前,我国正在综合利用RS、GIS与GPS技术、计算机与通信等技术进行第一次地理国情普查。弹性伸缩控制技术,是指对一个系统适应负载变化进行调控的能力。在同一个逻辑单元内增加资源,提高处理能力,即纵向可伸缩;增加多个逻辑单元资源,利用弹性伸缩控制技术令其如同在一个单元里工作,即横向可伸缩。应用虚拟化技术,可使弹性伸缩控制技术的优势发挥得更加充分。由于地理国情普查工作中信息负载曲线波动很大,弹性伸缩的需求是刚性、动态的。应用弹性伸缩控制技术整合动态负载均衡及资源配置机制,提高了资源利用率和用户满意度,实现了大规模系统的有效管理,在地理国情普查工作中有良好的应用前景。     

基于集群技术的“天地图”运行支持环境设计

在分析基于互联网的地理信息在线服务特点和网站服务质量需求的基础上,对服务器高可用性、负载均衡技术与构建方式、调度算法进行了讨论,给出了天地图网站高可用性服务器集群和负载均衡服务器集群的设计模型,描述了相关的设备部署、调度算法和健康性检测等方面的设计内容;同时,讨论了文件和关系型数据库服务器集群的具体应用。     

协同虚拟环境构建中的云计算应用研究

云计算是下一代网络计算的核心技术,它能提供可靠安全的数据运算、共享、开发利用,以及存储的网络服务。以各种网络为基础建立的专用云基本服务模式,不仅能解决协同虚拟环境构建过程中海量数据的运算处理、存储共享和网络传输问题,而且也能解决各种资源的动态分配和负载平衡等诸多问题,为协同虚拟环境的构建提供了一种新的思路和方法。     

Web Server集群技术

以LVS为例构建了一个集群系统，对部分LVS核心程序进行了修改，并加入了一种新的分配算法，在试验中取得了较好的效果。     

基于AIC准则的RBF神经网络在GPS高程拟合中的应用

本文采用AIC准则优化RBF神经网络参数的方法进行GPS高程拟合,在建立网络模型过程中,对不同的聚类半径由最近邻聚类法求出不同类别的聚类数目及相应的聚类中心和初始扩展常数,通过对不同类别分别进行调整扩展常数的网络训练,求出其最小AIC值,再根据AIC准则确定结构最优的RBF网络模型。实验结果表明:这种方法为确定最优RBF网络模型的隐节点数目及相应参数提供了途径;拟合精度较高,在较平坦测区可以替代三等水准测量。     

一种面向CPU/GPU异构环境的协同并行空间插值算法

CPU/GPU异构混合系统是一种新型高性能计算平台,但现有并行空间插值算法仅依赖CPU或GPU进行加速,迫切需要研究协同并行空间插值算法以充分利用异构计算资源,进一步提升插值效率。以薄板样条函数插值为例,提出一种CPU/GPU协同并行插值算法以加速海量激光雷达（light detector & ranger,LiDAR）点云生成数字高程模型（DEM）。通过插值任务的分解与抽象封装以屏蔽底层硬件执行模式的差异性,同时在多级协同并行框架基础上设计了Greedy-SET动态调度策略,策略顾及底层硬件能力的差异性,以实现异构并行资源的充分利用和良好负载均衡。实验表明,协同并行插值算法在高性能工作站上取得19.6倍的加速比,相比单一CPU或GPU并行算法,其效率提升分别达到54%和44%,实现了高效的协同并行处理。     

一种基于线性变换遗传算法的VOD集群负载均衡方法

对VOD集群中的负载均衡技术进行了分析和探讨，提出了一种基于线性变换遗传算法LTGA的负载均衡方法。实验结果表明，LTGA算法优于普通GA和WLCA算法。     

Adopting cloud computing to optimize spatial web portals for better performance to support Digital Earth and other global geospatial initiatives

A spatial web portal (SWP) provides a web-based gateway to discover, access, manage, and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and spiking. Although various technologies have been adopted to improve SWP performance, enabling high-speed resource access for global users to better support Digital Earth remains challenging because of the computing and communication intensities in the SWP operation and the dynamic distribution of end users. This paper proposes a cloud-enabled framework for high-speed SWP access by leveraging elastic resource pooling, dynamic workload balancing, and global deployment. Experimental results demonstrate that the new SWP framework outperforms the traditional computing infrastructure and better supports users of a global system such as Digital Earth. Reported methodologies and framework can be adopted to support operational geospatial systems, such as monitoring national geographic state and spanning across regional and global geographic extent.     

基于相容性任务分配的三维建模集群方法

针对现有集群方法在倾斜影像三维建模时节点上存在的CPU和GPU资源浪费现象及三维建模效率不高等问题,本文提出了基于相容性任务分配的集群三维建模方法。首先,通过对三维重建任务进行两步提交划分,在建模效果不变的前提下提升集群的执行效率。然后,针对集群节点资源浪费现象,提出了相容性任务节点分配方式,实现了基于相容性任务分配的三维建模集群。最后,进行大规模影像三维重建试验测试,验证了大数据试验环境下相容性理论对分配方式优化的优越性,证明了本文方法对三维建模效率有明显提升作用。     

Inferring the home locations of Twitter users based on the spatiotemporal clustering of Twitter data

Residential locations play an important role in understanding the form and function of urban systems. However, it is impossible to release this detailed information publicly, due to the issue of privacy. The rapid development of location‐based services and the prevalence of global position system (GPS)‐equipped devices provide an unprecedented opportunity to infer residential locations from user‐generated geographic information. This article compares different approaches for predicting Twitter users' home locations at a precise point level based on temporal and spatial features extracted from geo‐tagged tweets. Among the three deterministic approaches, the one that estimates the home location for each user by finding the weighted most frequently visited (WMFV) cluster of that user always provides the best performance when compared with the other two methods. The results of a fourth approach, based on the support vector machine (SVM), are severely affected by the threshold value for a cluster to be identified as the home.