服务器集群负载均衡技术研究及算法比较

简要介绍了负载均衡技术的分类及其发展,重点介绍了服务器集群负载均衡技术及应用.并对评价负载均衡优劣的重要标准之一--负载均衡算法的种类做了详细介绍及优缺点比较.对近年来一些新的负载均衡算法做了介绍.最后,对服务器集群负载均衡技术的发展前景做出了展望和预测.     

分布式均衡算法在防火墙集群中的实现

集中式的负载均衡算法虽然能提高防火墙集群系统的工作效率,但是负载平衡服务器本身承担了信息收集和权值计算等任务,会成为网络流量新的瓶颈。分布式负载均衡算法,将各结点信息的收集和权值的计算等项任务交由结点机自己完成,结点机主动将计算出的指标值定期发送给负载均衡服务器。负载均衡服务器只运行负载均衡算法来均衡网络访问,减少了中心负载均衡服务器的工作量,更有效地提高了防火墙集群系统的工作效率。     

LVS负载均衡调度算法的改进及实现

采用服务器集群架构提供服务成为互联网服务业中普遍采用的策略,目前使用得比较广泛的网络负载均衡集群是Linux虚拟服务器集群。优秀的负载均衡算法可以将用户请求合理地分配到集群中的真实服务器中．提高集群中服务器的利用率和集群系统的吞吐量。针对LVS默认算法WLC算法的不足之处,对WLC算法进行改进．设计并实现一种基于反馈式的负载均衡算法。实验证明,改进算法能够增大集群的吞吐量,提升集群的整体性能。     

服务器负载均衡技术研究

负载均衡是建立在网络结构之上的一种调度策略,能有效的扩展服务器带宽和增加吞吐量,增强网络数据处理能力。根据实际层次不同,对负载均衡技术进行了分类,从应用范围、运行原理等角度分析并比较了常用的负载均衡技术和算法,展望了负载均衡的发展。     

一种复合式的负载均衡方案探究

负载均衡技术可减轻大数据量的处理需求给服务器集群带来的巨大压力。本文对现有负载均衡技术和Linux服务器集群算法进行了分析,并依此为基础,探讨一种复合式的负载均衡方案。该方案融合了基于请求内容和IP隧道的负载均衡的优点,采用客户端和旁路负载均衡器相配合的结构,可进一步提高集群性能,提高资源利用率。     

基于Nginx服务器负载均衡技术的研究与改进

为了减轻快速增长的网络负载压力,本文为web后端服务器集群搭建了基于Nginx的负载均衡服务器[1],将其作为集群的反向代理服务器,使集群具备了负载均衡的功能,对负载均衡算法进行了分析。并针对Nginx自带负载均衡策略的缺陷提出了一种动态自适应负载均衡算法[2-5]-改进型加权最小连接数算法,同时对其算法进行了设计。测试的实验结果验证了改进型加权最小连接数算法的可行性[6]。     

一种改进的集群动态负载均衡算法

在集群系统的研究中,负载均衡算法是一个重要的方向,因为它关系到多台服务器在整合成一个集群系统后能否很好地相互协作,以更好地完成用户交予的任务。为实现上述目的,本文在分析已有的负载均衡算法基础上,提出一种改进的能够实时收集服务器负载指标,进而动态地计算出服务器在分配用户连接中的权重的方法。测试结果表明,该方法能够有效地防止服务器倾斜,达到良好的负载均衡效果。     

一种基于内容的Web集群服务器负载均衡算法

提出了一种基于内容的Web集群服务器负载均衡算法，该算法通过引入一个衡量不同内容任务量井利用当前真实节点上的连接数和请求内容的任务量以及真实节点的处理能力来调整服务器负载。同时，算法引入了一个反馈环节，将真实节点的负载信息反馈到负载均衡器，让负载均衡器调整自己的负载均衡策略，提高它的自适应能力。     

基于服务器实时性能状态的动态负载均衡算法

为实现Web服务器集群合理的作业任务分配,文章提出了一种新的负载均衡算法,综合考虑了负载均衡调度器后端的业务主机的实时性能,实现了负载均衡调度的动态调整.     

Web集群系统负载均衡策略分析与研究

Web集群技术是解决Web服务器系统容量和伸缩能力的重要方法。该文分析了影响Web集群系统性能的主要因素,并提出了一种基于内容的负载均衡算法。该算法以加权负载量来评估服务器负载状态,并通过保证负载局部性来提高cache命中率,从而获得好的负载均衡效果。仿真实验证明,该算法具有较好的适应能力和伸缩性。     

An approximation-based load-balancing algorithm with admission control for cluster web servers with dynamic workloads

The growth of web-based applications in business and e-commerce is building up demands for high performance web servers for better throughputs and lower user-perceived latency. These demands are leading to a widespread substitution of powerful single servers by robust newcomers, cluster web servers, in many enterprise companies. In this respect the load-balancing algorithms play an important role in boosting the performance of cluster servers. The previous load-balancing algorithms which were designed for the handling of static contents in web services suffer from significant performance degradation under dynamic and database-driven workloads. Regarding this, we propose an approximation-based load-balancing algorithm with admission control for cluster-based web servers in this study. Since it is difficult to accurately determine the loads of web servers through feedbacks from distributed agents in web servers, we propose an analytical model of a web server to estimate the web servers’ loads. To achieve this, the algorithm classifies requests based on their service times and track numbers of outstanding requests for each class of each web server node and also based on their resource demands to dynamically estimate the loads of each node. For the error handling of the model a proportional integral (PI) controller from control theory is used. Then the estimated available capacity of each web server is used for load balancing and admission control decisions. The implementation results with a standard benchmark confirm the effectiveness of the proposed scheme, which improves both the mean response time and the throughput of the cluster compared to rival load-balancing algorithms, and also avoids situations in which the cluster is overloaded, even when the request rates are beyond the cluster capacity.     

A predictive and probabilistic load-balancing algorithm for cluster-based web servers

The exponential demands for high performance web servers led to use of cluster-based web servers. This increasing trend continues as dynamic contents are changing traditional web environments. Increasing utilization of cluster web servers through effective and fair load balancing is a crucial task specifically when it comes to advent of dynamic contents and database-driven applications on the internet. The proposed load-balancing algorithm classifies requests into different classes. The algorithm dynamically selects a request from a class and assigns the request to a server. For both the scheduling and dispatching, new probabilistic algorithms are proposed. To avoid using unreliable measured utilization in the face of fluctuating loads the proposed load-balancing algorithm benefits from a queuing model to predict the utilization of each server. We also used a control loop feedback to adjust the predicted values periodically based on soft computing techniques. The implementation results, using standard benchmarks confirms the effectiveness of proposed load-balancing algorithm. The algorithm significantly improves both the throughput and mean response time in contrast to two existing load-balancing algorithms.     

对象存储系统中自适应的元数据负载均衡机制

面向对象的存储系统在研究、工程以及服务领域均得到了广泛的应用.在面向对象的存储系统中,元数据的负载均衡对于提高整个系统的I/O性能具有重要的作用.现有的元数据负载均衡策略不能动态地平衡元数据的访问负载,而且自适应性以及容错特性有待提高.提出了一种自适应的分布式元数据负载均衡机制(adaptabledistributed load balancing of metadata,简称ADMLB),包含基本的负载均衡算法和分布式的增量负载均衡算法.采用基本的负载均衡算法按照服务器的性能公平地分布负载,使用分布式的负载均衡算法定时地调整负载的分布.ADMLB采取分布式的方法均衡地在元数据服务器之间分布负载,根据负载的变化自适应地进行调整,具有很好的容错特性,而且用户可以高效地定位元数据服务器.     

基于集群的负载平衡调度算法研究与实现

在集群系统的负载调度研究中，针对请求的服务时间变化大的特点，该文提出了一个动态反馈负载平衡算法，它结合内核中的加权连接调度算法，根据动态反馈回来的负载信息来调整服务器的权值，从而有效地解决服务器问的负载不平衡问题，提高了系统的吞吐率。     

Efficient, proximity-aware load balancing for DHT-based P2P systems

Many solutions have been proposed to tackle the load balancing issue in DHT-based P2P systems. However, all these solutions either ignore the heterogeneity nature of the system, or reassign loads among nodes without considering proximity relationships, or both. In this paper, we present an efficient, proximity-aware load balancing scheme by using the concept of virtual servers. To the best of our knowledge, this is the first work to use proximity information in load balancing. In particular, our main contributions are: 1) relying on a self-organized, fully distributed k-ary tree structure constructed on top of a DHT, load balance is achieved by aligning those two skews in load distribution and node capacity inherent in P2P systems - that is, have higher capacity nodes carry more loads; 2) proximity information is used to guide virtual server reassignments such that virtual servers are reassigned and transferred between physically close heavily loaded nodes and lightly loaded nodes, thereby minimizing the load movement cost and allowing load balancing to perform efficiently; and 3) our simulations show that our proximity-aware load balancing scheme reduces the load movement cost by 11-65 percent for all the combinations of two representative network topologies, two node capacity profiles, and two load distributions of virtual servers. Moreover, we achieve virtual server reassignments in O(log N) time.     

An SSL Back-End Forwarding Scheme in Cluster-Based Web Servers

State-of-the-art cluster-based data centers consisting of three tiers (Web server, application server, and database server) are being used to host complex Web services such as e-commerce applications. The application server handles dynamic and sensitive Web contents that need protection from eavesdropping, tampering, and forgery. Although the secure sockets layer (SSL) is the most popular protocol to provide a secure channel between a client and a cluster-based network server, its high overhead degrades the server performance considerably and, thus, affects the server scalability. Therefore, improving the performance of SSL-enabled network servers is critical for designing scalable and high-performance data centers. In this paper, we examine the impact of SSL offering and SSL-session-aware distribution in cluster-based network servers. We propose a back-end forwarding scheme, called ssl_with_bf, that employs a low-overhead user-level communication mechanism like virtual interface architecture (VIA) to achieve a good load balance among server nodes. We compare three distribution models for network servers, round robin (RR), ssl_with_session, and ssl_with_bf, through simulation. The experimental results with 16-node and 32-node cluster configurations show that, although the session reuse of ssl_with_session is critical to improve the performance of application servers, the proposed back-end forwarding scheme can further enhance the performance due to better load balancing. The ssl_with_bf scheme can minimize the average latency by about 40 percent and improve throughput across a variety of workloads.     

网络负载均衡在Web服务器中的应用

网络负载均衡是一种动态均衡技术,也是提高网络可靠性、进行高性能计算以及实现网络负载合理均衡分配的关键技术,它能将工作负载在多个配置和性能相近的服务器间进行均衡分配,保证网络高效运行。服务器群集使得网络负载均衡能力得到极大改善,在Windows Server 2003中网络负载均衡功能易于操作实现。本文介绍了Windows Server 2003网络负载均衡技术在Web网站的应用案例。     

Global web server load balancing using evolutionary computational techniques

 As user load on web servers becomes more globalised, duplicated regional mirroring is being seen as an increasingly expensive solution to meeting regional peak demand. Alternative solutions are being explored by looking at dynamic load balancing using distributed intelligent middleware to re-route traffic from busy regions to quieter ones as global load patterns change over a 24 h cycle. The techniques used can also be employed under fault and planned maintenance conditions. One such solution, providing the load balancing via reconfigurable dynamic proxy servers, is seen as `unobtrusive' in that it works with standard web browsers and web server technology. The technique employs an evolutionary algorithm to perform combinatorial optimisation against a dynamic performance predicting model. This paper describes this solution, focussing on issues such as algorithm tuning, scalabilty and reliability. A prototype system is currently being trialled within the Systems Integration Department at British Telecommunications Research Labs, Adastral Park and is the subject of several BT held patents.