利用Iptables实现LVS负载均衡集群研究

集群是一组相互独立的、通过高速网络互连的计算机,利用集群技术构建的服务器集群具有高可扩展性,高可用性,高性能和高性价比等优点.文章分析了LVS虚拟服务器的工作原理,给出了基于IP层的负载均衡调度和Iptables的包转发技术构建LVS负载均衡集群的具体方案,并结合RedHat Linux操作系统进行了实现.     

基于软交换的异构集群媒体服务器中一种LRV负载均衡算法

针对基于软交换的集群媒体服务器的系统特征,本文提出了一种LRV(Limited Resource Vector)负载均衡算法,该算法考虑了系统中资源的协调使用并有效防止了系统性能的剧烈变化.通过在集群媒体服务器负载均衡系统Petri网模型上的大量仿真模拟,对LRV负载均衡算法与其他传统负载均衡算法在异构环境下的均衡能力、系统吞吐量、系统响应时间和性能平稳性几个方面做了比较和分析.结果表明,LRV算法具有优越的性能,对集群媒体服务器的异构环境有良好的适应能力.     

基于软件定义网络的服务器集群负载均衡技术研究

在当前的网络体系结构下,采用硬件系统实现服务器集群负载均衡存在着获取负载节点状态困难、流量导向方式复杂等制约因素,不利于提升服务器集群的伸缩性和服务性能。针对此问题,该文提出一种基于软件定义网络(SDN)的负载均衡机制(SDNLB)。该机制借助SDN具有的集中式控制和流量灵活调度优势,利用SNMP协议和OpenFlow协议对服务器的运行状态和全局网络负载信息进行实时监测,并通过权值计算的方式选择出权重最高的服务器作为流处理的目标服务器,在此基础上,采用最优转发路径算法进行流量调度,从而达到提高服务器集群的利用率与处理性能的目的。搭建了实验平台对SDNLB的性能进行仿真测试,实验结果表明:在相同的网络负载条件下,SDNLB与其他负载均衡算法相比,能够有效地降低服务器集群的负载,并能够显著提高网络吞吐量和带宽利用率,缩短流的完成时间和平均时延。     

基于mean-variance的服务集群负载均衡方法

大量并发请求任务进行分配时,负载调度机制是通过最小化响应时间及最大化节点利用率实现网络中节点的负载均衡,在基于遗传算法的负载均衡算法中,适应度函数设计对服务集群负载均衡效率产生重要的影响.对此提出了一种基于mean-variance的服务集群负载均衡方法对适应度函数进行优化,采用投资组合选择模型mean-variance进行最小化响应时间,以得到每个服务器资源利用率的权重,从而获得最优的分配组合,进而提高适应度函数的准确性和有效性.在不同服务环境下与其他模型进行比较,仿真结果表明,本文的负载均衡算法在节点利用率和响应时间方面使服务集群得到了更好的均衡.     

Cache虚拟服务器集群中IP负载均衡技术研究

网络Cache系统可以大大地减少网络流量、降低响应延时以及服务器的负载，通过虚拟服务器构造Cache服务器集群对外提供缓存服务，具有很好的可用性和可扩展性，其中最关键的技术是如何实现各个服务器之间的负载均衡。本文讲述了IP负载均衡技术及如何基于LVS构造高效率Cache服务器集群，最后对虚拟服务器的应用前景进行了展望。     

基于改进布谷鸟算法的自适应负载均衡算法

针对负载均衡算法在高负载请求下服务器集群效率不高,负载不均衡及低负载请求下影响服务器效率的问题,文中基于Nginx负载均衡服务器,提出一种基于改进布谷鸟算法的自适应负载均衡算法。该算法通过熵权法确定CPU、内存、磁盘IO性能和网络带宽等各项负载指标的权系数,衡量各项负载指标对负载评价影响的重要程度,并基于Nginx加权轮询算法和服务器实时负载情况,设计了高并发负载情况下的动态负载均衡算法。引入转化阈值计算,通过引入基于种群熵的改进布谷鸟算法计算Nginx静态加权轮询算法,转变为动态负载均衡算法的转化阈值。通过实验测试,相较于WRR算法、least-con算法和动态权重算法,该算法在响应时间和实际并发数等方面具有表现更好,在数值上相比于动态权重算法有18%左右的提升,验证了本文算法具有更好的负载均衡效果。     

基于DHCP服务器状态的动态负载均衡算法

负载均衡是DOCSIS/PacketCable网络环境中DHCP服务集群亟待解决的问题,负载均衡算法是给集群中各服务器分配任务的核心,本文提出了一种根据服务器状态来分配任务的算法,给出了服务器性能、负载量、权值及服务器状态的计算。算法引入了根据随机数和服务器的状态选择服务器的方法,在考虑服务器真实负载,处理能力的基础上,尽量简化负载均衡器的任务分配算法。测试结果显示该算法优于基于实时性能动态反馈的负载均衡算法。     

电子商务系统集群综合QoS控制算法

电子商务系统运用越来越广泛,但网络流量的指数性增长和服务器的数据处理能力并未得到相应的增长,极大地制约了电子商务的实际应用以及网络性能和扩展。集群技术是一种先进的技术,文章对集群负载均衡算法进行了分析探讨,提出了一种基于请求的优先化调度和服务器集群的Content-aware动态负载均衡相结合的综合QoS控制方法,最后我们将该集群技术综合QoS控制机制应用到一种基于CDMA技术的电子商务系统,并在实际应用中取得了极佳的性能。     

Web服务器的网络负载均衡研究

介绍了网络负载均衡的定义和总体指标.详细讨论了网络负栽均衡技术的4种类型.针对不同Web服务器的架构.分析了服务器的吞吐量和网络延迟,其结论对于有效提高服务器的整体性能、服务质量和服务水平具有参考意义.     

基于控制器集群的SDON多域互联互通技术北大核心

针对软件定义光网络(SDON)多控制域互联互通的需求,在对多控制域信息交互协同控制进行分析研究的基础上,利用负载均衡的思想,提出了一种基于控制器集群的SDON多控制域互联互通架构,包含集群间和集群内两个互联层次。利用集群间控制器迁移和集群内主从控制器切换机制,实现光网络中多控制域间的协同互联和负载均衡,提升网络服务质量。     

基于排队论综合指标评估的动态负载均衡算法

互联网通信、计算机集群和云环境均具有一定的复杂性和动态性,极易发生负载失衡,从而降低服务效率、增加能耗。因此,负载均衡技术成为重点研究课题。现有的负载均衡策略均是以 CPU、内存、进程等参数的占用率来评估服务器当前的负载情况,但服务器负载情况的复杂性往往使其难以得到准确评估。针对该问题,提出了一种基于排队论综合指标评估的动态负载均衡算法,首先引入排队论模型评估各服务器的实时负载情况,然后根据各服务器的负载综合指标,将输入队列中的任务逐一分配给各服务器。实验结果表明,该方法可有效平衡各服务器的负载且减少任务请求的平均等待时间。     

Research on scheduling method based on traffic matrix for IoT security

With the increasing number of sensors in the Internet of Things (IoT), network nodes are prone to load imbalance, which seriously affects the reliability and scalability of the IoT. In this paper, a method of load balancing is proposed to reduce the pressure of switches in IoT and improve the efficiency of switch. The method is based on software defined network (SDN) technology using dynamic traffic scheduling of server cluster (DTSSC) model. It obtains the traffic and load matrices for each server and achieves load balancing on each of them. This method has high efficiency and low overhead and is easy to deploy. The validity of this method is verified through experiments; ie, the load ratio of each server is balanced.     

Estimation‐Based Load‐Balancing with Admission Control for Cluster Web Servers

The growth of the World Wide Web and web‐based applications is creating demand for high performance web servers to offer better throughput and shorter user‐perceived latency. This demand leads to widely used cluster‐based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database‐driven workloads. We propose an estimation‐based load balancing algorithm with admission control for cluster‐based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.     

DServ‐LB: Dynamic server load balancing algorithm

In recent years, web services have been largely accessed by the customer, and it increases the network traffic on the internet. To provide the services for the large number of customer, dynamic clustering concept has been implemented that provides the ability to add or remove the servers on demand. But managing and processing the large set of traffic are very complicated. Load balancing technic helps to resolve the problems of network traffic and give efficient network management. In this paper, we proposed a dynamic server load balancing algorithm (DServ‐LB) using OpenFlow switches in software‐defined networking. The OpenFlow switches support the dynamic programmability. Also, we used the sFlow protocol, which is used to monitor the servers resource information periodically and the controller. Based on the server resource availability, the controller installs forwarding rules in the OpenFlow switches. For implementation, we used Mininet for network emulation, POX controller, and Docker container as Mininet hosts. The result shows that the proposed DServ‐LB improves the overall network performance and efficiently utilizes the server resources if compared with existing load balancing algorithms.     

GOP-SDN: an enhanced load balancing method based on genetic and optimized particle swarm optimization algorithm in distributed SDNs

Wireless Networks - One of the biggest challenges of distributed software defined networks (SDNs) is to create load balancing on controllers to reduce response time. Although recent studies have...     

An Efficient Gaming User Oriented Load Balancing Scheme for MMORPGs

Massively multi-player online role-playing games (MMORPGs) follows a client-server model that has the numerous gaming users with many interactions at the same virtual world, massive loading that result in delays, resource shortages, and other such problems occur. Also, faced with high resource demand variability and with misfit resource renting policies, the current practices is to overprovision for each game tens of owned data. Existing load balancing schemes for distributed virtual environments and multiplayer games try to balance the workload among servers by transferring some workload of an overloaded server to other servers. While load balancing algorithms can minimize the average response time of the system, they may also result in frequent client migrations, which may damage the interactivity of an online games. To solve this, many developers devote research to load-balancing servers, yet due to steady and dynamic map divisions, such research is unreliable. Many developers propose algorithms to distribute the load on the server nodes, but the load is usually defined as the number of players on each server, what is not an ideal results. So, we propose a gaming user-oriented load balancing scheme for the load balancing of MMORPGs servers in this paper. This scheme shows effectiveness at dealing with hot-spots and other gatherings of gaming users at specific servers compared to previous methods.     

负载均衡集群技术在企业级PDM系统平台的应用

为了确保企业应用系统在大流量的客户端请求下,在提高网络速率有限的情况下,能承受客户端大量并发访问请求,尽可能大地提高系统的处理能力以及高稳定性。本文提供了以负载均衡集群技术为系统平台架构的方案。该方案以产品管理系统软件为应用软件,安装配置结合使用小型服务器热备机制、负载均衡技术以及数据库均衡技术一同实现的系统平台架构。从系统平台底层,改变传统单台系统服务器的使用压力,均衡分配对系统服务的访问负载量,排除单点故障瓶颈,提高整体系统访问速度和工作的生产效率。     

SDN中基于效能优化的交换机动态迁移策略

交换机迁移作为一种弹性控制方式对于软件定义网络（SDN）中多控制器负载均衡具有重要作用.针对现有迁移方案存在迁移效率低下和高迁移代价问题，提出基于效能优化的交换机动态迁移策略.首先，分析控制器负载组成并构建负载差异矩阵，设置触发因子进行负载不均衡判定.然后确定迁移对象，建立迁移效能模型，同时考虑负载均衡率和迁移代价来确定迁移交换机和迁入控制器.最后，通过设定迁移三元组完成迁移映射，实现高效交换机迁移.仿真结果表明，该策略可以有效降低控制器响应时间，减小迁移代价并提高控制器吞吐量，同时将负载均衡率保持在较高水平，具有良好的拓扑适应性.     

Traffic pattern–based load‐balancing algorithm in software‐defined network using distributed controllers

Programmability and decoupling of the data plane and control plane in software‐defined networking (SDN) make the enterprise's network to focus on this new paradigm and to deploy their applications on it. Furthermore, supporting of distributed controllers in SDN opens the opportunities to address the limitations of centralized controller's architecture, which in turn improves the overall performance of the network. This study proposes a new load‐balancing algorithm to handle the load based on the traffic pattern specifically transmission control protocol (TCP) and user datagram protocol (UDP) traffic. Additionally, this study uses a distributed SDN controller's architecture to host the load balancer application. This study also employs a failover mechanism on the distributed architecture to achieve high‐availability environment and to ensure the redundancy and reliability of the network. The obtained results prove the effectiveness of the proposed algorithm in terms of availability, which is increased by 11%, response time is reduced by 98%, transaction rate is also increased by 258%, throughput is increased by 206%, concurrency is reduced by 63%, and packet loss is reduced by 86% while comparing with random, round‐robin, and weighted round‐robin algorithms in addition to ease the integration and deployment in distributed controllers.