基于OpenResty的一种自定义负载均衡算法

为了解决服务器集群中负载调度不均衡导致高并发情况下服务器响应时间过长以及实际并发数过低的问题,提出一种基于加权轮询算法以及层次分析法（Analystic Hierarchy Process,AHP）的自定义请求类型负载均衡算法。首先收集服务器集群的负载信息,其次定时与负载均衡服务器通信,同步集群节点的负载情况,最后根据请求类型使用对应的权重。实验结果表明,文章提出的算法能够有效应对高并发情形。     

ALAD动态负载均衡算法研究

针对现有服务器集群的负载平衡算法不足,提出一种应用层自适应动态负载平衡算法。利用应用层特点,在负载均衡服务器端收集应用服务器负载信息,提出一种综合的权重计算方法,动态区分不同状态的服务器。通过自适应选择算法,合理分配请求至应用服务器。实验结果表明,在不同的负载情况下,该算法能有效地平衡负载,充分利用服务器资源。     

基于粗糙集的负载均衡算法研究

在负载均衡服务器集群中,负载均衡算法是一个关键部分。针对目前服务器集群使用的负载均衡算法所存在的缺陷:服务器可能出现较大倾斜,本文提出了一种基于粗糙集理论的动静结合的负载均衡算法。该算法避免了服务器间负载的不均衡,能有效地防止服务器倾斜的发生,提高了集群系统的整体性能。     

分布式文件系统的动态负载均衡算法

为了解决分布式文件系统的负载均衡问题,研究了多种负载均衡算法,分析各种算法的优缺点.综合了静态权重轮询算法和动态负载均衡算法两类算法的优点,提出一种自适应的综合动态负载均衡算法,它实现简单、降低了获取反馈信息的开销且不失实时性.经过试验比较,该算法能有效地降低平均响应时间和提高吞吐量,负载的分配更为均衡.     

基于动态反馈的负载均衡算法

负载均衡服务器集群中,负载均衡算法是一个关键的部分,它是集群系统中任务分配的核心环节。任务分配的主要因素包括服务节点的处理能力与服务节点实际负载两个部分。本文所讨论的负载均衡算法综合了这两方面的影响,引入了节点负载增量对服务节点实际负载进行预测,以求更精确地表示服务节点的负载情况;同时通过动态反馈机制实时修正,保证了系统在长时间运行时,负载不会发生倾斜。     

图书馆网络负载均衡技术研究

本文提出了一种新的负载均衡算法—基于负载率的调度算法,首先从理论上对该算法进行了分析,并与轮询调度算法进行优劣性比较。最后总结了新算法涉及的各参数对负载均衡情况的影响。     

使用动态负载均衡技术的LINUX高性能集群服务器研究

本文主要了应用动态均衡技术实现高性能集群服务器,其中包括虚拟服务器的概念以及虚拟服务器中的包转发模式和调度算法,经过实验研究总结了这种技术的优缺点,针对该技术的不足,提出了网络冗余部件、网络镜像和网络文件系统的解决方案。     

一种自适应动态负载均衡算法

负载均衡问题是一个经典的组合优化难题,该文建立了一个集群中的负载均衡问题模型,并提出了一种旨在最小化负载均衡开销的动态自适应算法。由于集群中存在网络延时,所以负载重分配的开销很大一部分取决于CPU间发送、接受的消息的最大数量。该负载均衡算法以最小化负载重分配时CPU间消息发送、接受的数量为目标,根据过载、轻载CPU数量的变化动态调用D算法和R算法,以降低负载均衡开销。     

服务器集群负载均衡策略的研究

针对服务器集群负载均衡的问题,兼顾任务调度跨度和负载均衡度,提出一种遗传模拟退火算法。实验结果表明,该算法降低了任务调度跨度,提高了集群系统的资源利用率和负载均衡度。     

一种基于动态反馈的负载均衡算法研究

集群的负载均衡策略是提高集群整体性能的关键。文章提出了一种基于资源使用率和输入参数的负载均衡算法，有效地解决了集群内各服务器间的负载均衡问题。     

SALSA: QoS-aware load balancing for autonomous service brokering

The evolution towards “Software as a Service”, facilitated by various web service technologies, has led to applications composed of a number of service building blocks. These applications are dynamically composed by web service brokers, but rely critically on proper functioning of each of the composing subparts which is not entirely under control of the applications themselves. The problem at hand for the provider of the service is to guarantee non-functional requirements such as service access and performance to each customer. To this end, the service provider typically divides the load of incoming service requests across the available server infrastructure. In this paper we describe an adaptive load balancing strategy called SALSA (Simulated Annealing Load Spreading Algorithm), which is able to guarantee for different customer priorities, such as default and premium customers, that the services are handled in a given time and this without the need to adapt the servers executing the service logic themselves. It will be shown that by using SALSA, web service brokers are able to autonomously meet SLAs, without a priori over-dimensioning resources. This will be done by taking into account a real time view of the requests by measuring the Poisson arrival rates at that moment and selectively drop some requests from default customers. This way the web servers’ load is reduced in order to guarantee the service time for premium customers and provide best effort to default customers. We compared the results of SALSA with weighted round-robin (WRR), nowadays the most used load balancing strategy, and it was shown that the SALSA algorithm requires slightly more processing than WRR but is able to offer guarantees - contrary to WRR - by dynamically adapting its load balancing strategy.     

基于权重轮询负载均衡算法的优化

随着电商网站用户规模不断增长,高并发问题成为在搭建大规模电商网站系统时面临的一项重大挑战,通过负载均衡算法来实现Web服务集群中各节点均衡负载是解决高并发的手段之一.然而,目前通用的负载均衡算法都存在一些不足之处,针对这一问题,提出了一种动态自适应权重轮询随机负载均衡算法（Dynamic Adaptive Weight Round-Robin Random Load-Balancing,DAWRRRLB）,该算法考虑到影响Web服务集群中服务器节点性能的多重因素,根据节点在运行过程中的实时负载情况动态的改变集群中节点的负载性能,并结合改进的Pick-K算法对权重轮询负载均衡算法进行优化,始终保证性能最优的服务器节点在提供服务.通过多次实验对比,改进的DAWRRRLB算法可以有效的提高负载均衡效率.     

双系统动态同步PID参数优化的模拟退火算法

PID控制是目前广泛应用于工业生产各个领域的控制方法.传统的PID参数整定方法,在解决双系统动态同步PID参数优化问题上遇到了很大的困难.将模拟退火算法应用于双系统动态同步PID参数优化的问题上,使用MATLAB工具对两个典型的二阶系统动态同步PID参数优化进行了仿真试验,两个系统的动态同步性能得到了明显的改善.此方法应用于机车定置试验台的同步控制中,取得了比较好的控制效果.仿真试验和实际应用都表明,模拟退火算法对解决双系统动态同步PID参数优化的问题是有效的,具有很强的实用价值.     

A simulated annealing algorithm based on block properties for the job shop scheduling problem with total weighted tardinessobjective

In modern manufacturing systems, due date related performance is becoming increasingly important in maintaining a high service reputation. However, compared with the extensive research on makespan minimization, research on the total weighted tardiness objective is comparatively scarce, partly because this objective function is more difficult and complex to optimize. In this paper, we focus on the job shop scheduling problem with the objective of minimizing total weighted tardiness. First, we discuss the mathematical programming model and its duality when the processing orders for each machine are fixed. Then, a block-based neighborhood structure is defined and its important properties are shown. Finally, a simulated annealing algorithm is designed which directly utilizes the features of this neighborhood. According to the computational results, the new neighborhood considerably promotes the searching capability of simulated annealing and helps it converge to high-quality solutions.     

A simulated annealing heuristic for the dynamic layout problem with budget constraint

Facility layout problem has been extensively studied in the literature because the total material handling cost can be a significant portion in the operational costs for a company and in the manufacturing cost of a product. Today’s severe global competition, rapid changes in technology and shortening life cycle of products force companies to evaluate and modify their facility layout in a periodic fashion. This type of layout problems is categorized as the dynamic facility layout problem (DFLP). As a realistic dimension of the problem, one has to consider also the limited budget to cover the cost of changing the layout. In this study, we propose a simulated annealing heuristic for the DFLP with budget constraint, and show the effectiveness of this heuristic on a set of numerical experiments.     

基于弯曲距离三支决策的时序相似性算法

动态时间弯曲距离算法(DTW)是目前公认的最有效的时间序列相似性计算方法之一,但是较高的时间复杂度一直是其主要缺点。快速弯曲距离算法(FTW)能有效提高DTW的计算速度,但是该算法对不同粒度时间序列剪枝的行为是典型的二支决策,与人类处理不确定问题时普遍采用的三支判断不同。因此,通过将三支决策理论引入到DTW算法的优化工作中,建立了DTW三支决策模型;然后对DTW三支决策模型中的决策阈值α和β进行了基于误识别率的推导,并且给出了具体求解阈值α和β的模拟退火算法;最后基于上述理论提出了基于弯曲距离三支决策的时序相似性算法(3WD-DTW)。通过对比实验表明,与FTW算法相比,3WD-DTW算法在保持较快的计算速度的前提下明显提升了计算准确度,使其接近DTW的水平。     

Design of bi-criteria kanban system using simulated annealing technique

In the kanban system, the main decision parameters are the number of kanbans and lot size. In this paper, an attempt has been made to set the number of kanbans at each station and the lot size required to achieve the best performance using simulated annealing technique. A simulation model with a single-card system has been designed and used for analysis. A bi-criterion objective function comprising of mean throughput rate and aggregate average kanban queue has been used for evaluation. Different perturbation schemes have been experimented and compared.     

大规模文件上传接收服务的负载均衡引擎研究

针对大规模网络环境下的文件上传接收服务系统的需求,设计了一个集群架构的文件接收服务系统,采用多台接收服务器来实现文件接收服务,提高了系统的稳定性和可用性。根据文件传输的特点,综合考虑文件流量负载情况和服务器当前负载情况,提出了一个综合负载统计的负载均衡算法,测试结果表明基于该算法的文件接收集群系统具有较好的负载均衡效果。设计并实现了文件上传接收服务系统的负载均衡引擎,解决了系统的负载失衡问题,提高了系统的运行效率。