DNS dispatching algorithms with state estimators for scalable Web‐server clusters

Replication of information across a server cluster provides a promising way to support popular Web sites. However, a Web‐server cluster requires some mechanism for the scheduling of requests to the most available server. One common approach is to use the cluster Domain Name System (DNS) as a centralized dispatcher. The main problem is that WWW address caching mechanisms (although reducing network traffic) only let this DNS dispatcher control a very small fraction of the requests reaching the Web‐server cluster. The non‐uniformity of the load from different client domains, and the high variability of real Web workload introduce additional degrees of complexity to the load balancing issue. These characteristics make existing scheduling algorithms for traditional distributed systems not applicable to control the load of Web‐server clusters and motivate the research on entirely new DNS policies that require some system state information. We analyze various DNS dispatching policies under realistic situations where state information needs to be estimated with low computation and communication overhead so as to be applicable to a Web cluster architecture. In a model of realistic scenarios for the Web cluster, a large set of simulation experiments shows that, by incorporating the proposed state estimators into the dispatching policies, the effectiveness of the DNS scheduling algorithms can improve substantially, in particular if compared to the results of DNS algorithms not using adequate state information. This revised version was published online in August 2006 with corrections to the Cover Date.     

Distributed cooperative Web servers

Traditional techniques for a distributed web server design rely on manipulation of central resources, such as routers or DNS services, to distribute requests designated for a single IP address to multiple web servers. The goal of the distributed cooperative Web server (DCWS) system development is to explore application-level techniques for distributing web content. We achieve this by dynamically manipulating the hyperlinks stored within the web documents themselves. The DCWS system effectively eliminates the bottleneck of centralized resources, while balancing the load among distributed web servers. DCWS servers may be located in different networks, or even different continents and still balance load effectively. DCWS system design is fully compatible with existing HTTP protocol semantics and existing web client software products.     

A performance study of robust load sharing strategies fordistributed heterogeneous Web server systems

Replication of information across multiple servers is becoming a common approach to support popular Web sites. A distributed architecture with some mechanisms to assign client requests to Web servers is more scalable than any centralized or mirrored architecture. In this paper, we consider distributed systems in which the Authoritative Domain Name Server (ADNS) of the Web site takes the request dispatcher role by mapping the URL hostname into the IP address of a visible node, that is, a Web server or a Web cluster interface. This architecture can support local and geographical distribution of the Web servers. However, the ADNS controls only a very small fraction of the requests reaching the Web site because the address mapping is not requested for each client access. Indeed, to reduce Internet traffic, address resolution is cached at various name servers for a time-to-live (TTL) period. This opens an entirely new set of problems that traditional centralized schedulers of parallel/distributed systems do not have to face. The heterogeneity assumption on Web node capacity, which is much more likely in practice, increases the order of complexity of the request assignment problem and severely affects the applicability and performance of the existing load sharing algorithms. We propose new assignment strategies, namely adaptive TTL schemes, which tailor the TTL value for each address mapping instead of using a fixed value for all mapping requests. The adaptive TTL schemes are able to address both the nonuniformity of client requests and the heterogeneous capacity of Web server nodes. Extensive simulations show that the proposed algorithms are very effective in avoiding node overload, even for high levels of heterogeneity and limited ADNS control     

Web服务器负载均衡的研究

目前的WWW负载均衡大多是通过分布式Web服务器的设计来实现的。而分布式Web服务器设计中的传统技术依赖于对中心资源的操纵（如路由器或DNS服务器）。本文是对目前负载均衡技术存在问题解决方案的进一步研究,研究的目的是探索基于应用的负载均衡Web服务器（Application Based Load Balancing Web Server),避免中心资源形成系统瓶颈。     

Request redirection algorithms for distributed Web systems

Replication of information among multiple servers is necessary to support high request rates to popular Web sites. We consider systems that maintain one interface to users, even it they consist of multiple nodes with visible IP addresses that are distributed among different networks. In these systems, first-level dispatching is achieved through the Domain Name System (DNS) during the address lookup phase. Distributed Web systems can use a request redirection mechanism as second-level dispatching because the DNS routing scheme has limited control on offered load. Redirection is always executed by the servers, but there are many alternatives that are worth investigating. We explore the combination of DNS dispatching with redirection schemes that use centralized or distributed control on the basis of global or local state information. In fully distributed schemes, DNS dispatching is carried out by simple algorithms because load sharing is taken by some redirection mechanisms that each server activates autonomously. On the other hand, in fully centralized schemes, redirection is used as a tool to enforce decisions taken by the same centralized entity that provides the first-level dispatching. We also investigate hybrid strategies. We conclude that distributed algorithms are preferable over their centralized counterpart because they provide stable performance, take content-aware dispatching decisions, limit the percentage of redirected requests, and their implementation is much simpler than that required by centralized schemes.     

On the Design of Distributed Object Placement and Load Balancing Strategies in Large-Scale Networked Multimedia Storage Systems

In a large-scale multimedia storage system (LMSS) where client requests for different multimedia objects may have different demands, the placement and replication of the objects is an important factor, as it may result in an imbalance in server loading across the system. Since replication management and load balancing are all the more crucial issues in multimedia systems, in the literature, these problems are handled by centralized servers. Each object storage server (OSS) responds to the requests that come from the centralized servers independently and has no communication with other OSSs in the system. In this paper, we design a novel distributed load balancing strategy for LMSS, in which OSSs can cooperate to achieve higher performance. Such OSS modeled as an M/G/m system can replicate the objects to and balance the requests among other servers to achieve a near-optimal average waiting time (AWT) of the requests in the system. We validate the performance of the system via rigorous simulations with respect to several influencing factors and prove that our proposed strategy is scalable, flexible, and efficient for real-life applications.     

Faster Web page allocation with neural networks

To maintain quality of service, some heavily trafficked Web sites use multiple servers, which share information through a shared file system or data space. The Andrews file system (AFS) and distributed file system (DFS), for example, can facilitate this sharing. In other sites, each server might have its own independent file system. Although scheduling algorithms for traditional distributed systems do not address the special needs of Web server clusters well, a significant evolution in the computational approach to artificial intelligence and cognitive engineering shows promise for Web request scheduling. Not only is this transformation - from discrete symbolic reasoning to massively parallel and connectionist neural modeling - of compelling scientific interest, but also of considerable practical value. Our novel application of connectionist neural modeling to map Web page requests to Web server caches maximizes hit ratio while load balancing among caches. In particular, we have developed a new learning algorithm for fast Web page allocation on a server using the self-organizing properties of the neural network (NN).     

A testbed for performance evaluation of load‐balancing strategies for Web server systems

To improve response time of a Web site, one replicates the site on multiple servers. The effectiveness of a replicated server system will depend on how the incoming requests are distributed among replicas. A large number of load‐balancing strategies for Web server systems have been proposed. In this paper we describe a testbed that can be used to evaluate the performance of different load‐balancing strategies. The testbed uses a general architecture which allows different load‐balancing approaches to be supported easily. It emulates a typical World Wide Web scenario and allows variable load generation and performance measurement. We have performed some preliminary experiments to measure the performance of a few policies for load balancing using this testbed. Copyright © 2003 John Wiley & Sons, Ltd.     

一种资源优化的双最小均衡Web集群区分服务调度算法

在一种新的Web集群体系结构的基础上,提出了一种资源优化的双最小均衡区分服务调度算法：首先在前端调度器按资源均衡度将Web请求分配到各后台服务器．然后将Web请求的优先级与资源均衡度两个特征参数结合起来,综合设计后台服务器的Web请求调度顺序,为了评估该算法的性能,进行了大量的模拟实验．在与其他著名调度策略如分离式调度的对比结果显示：双最小均衡调度算法使Web请求的效率提高了11％,同时很好地实现了区分服务．证实了资源优化调度策略具有一定的普遍意义．     

Dynamic load balancing on Web-server systems

Popular Web sites cannot rely on a single powerful server nor on independent mirrored-servers to support the ever-increasing request load. Distributed Web server architectures that transparently schedule client requests offer a way to meet dynamic scalability and availability requirements. The authors review the state of the art in load balancing techniques on distributed Web-server systems, and analyze the efficiencies and limitations of the various approaches     

Load sharing in distributed multimedia-on-demand systems

Service providers have begun to offer multimedia-on-demand services to residential estates by installing isolated, small-scale multimedia servers at individual estates. Such an arrangement allows the service providers to operate without relying on a highspeed, large-capacity metropolitan area network, which is still not available in many countries. Unfortunately, installing isolated servers can incur very high server costs, as each server requires spare bandwidth to cope with fluctuations in user demand. The authors explore the feasibility of linking up several small multimedia servers to a (limited-capacity) network, and allowing servers with idle retrieval bandwidth to help out servers that are temporarily overloaded; the goal is to minimize the waiting time for service to begin. We identify four characteristics of load sharing in a distributed multimedia system that differentiate it from load balancing in a conventional distributed system. We then introduce a GWQ load sharing algorithm that fits and exploits these characteristics; it puts all servers' pending requests in a global queue, from which a server with idle capacity obtains additional jobs. The performance of the algorithm is captured by an analytical model, which we validate through simulations. Both the analytical and simulation models show that the algorithm vastly reduces wait times at the servers. The analytical model also provides guidelines for capacity planning. Finally, we propose an enhanced GWQ+L algorithm that allows a server to reclaim active local requests that are being serviced remotely. Simulation experiments indicate that the scheduling decisions of GWQ+L are optimal, i.e., it enables the distributed servers to approximate the performance of a large centralized server     

一种基于OSI应用层的Web群集负载平衡调序策略研究

本文总结了目前基于L7的Web群集负载平衡调度研究，分析了影响性能的主要因素，在估计Web负载时考虑了请求强度以及Web服务器自身的性能，提出了处理能力异构服务器群集的最小负载调度算法。在算法中还同时考虑了服务器在进入临界状态时性能急剧下降的因素，避免群集进入临界状态．新算法能较为准确地跟踪群集系统的负载，更好地
均衡分配负载。     

WEB服务器的负载研究与处理

WEB服务器过载是导致“网络拥塞”的根源,严重制约了动态Web技术的应用和发展。文章通过改变IIS服务器程序处理过程,,利用分布式缓冲池页面处理方式,结合调度池算法和重定向技术,提出了一种ISAPI的自适应负载均衡处理系统集成方案,减轻Web服务器的负载,加速并均衡了对客户的响应,大大缓解了“网络拥塞”现象。     

Web服务器集群系统的实现方法及负载管理

影响WWW网站应用的一个主要因素是用户请求的响应时间太慢,这严重影响了基于Internet的各项应用的发展。本文主要阐述了如何通过多个分布式的Web服务器结点来构筑Web服务器集群系统。文中详细说明了Web服务器集群系统的实现原理及方法,并讨论提出了实出其中各个服务结点之间负载平衡的一些基本技术及机制。     

基于Nginx负载均衡的动态改进算法

随着过去几十年互联网服务的指数增长,各大网站的访问量急剧上升。海量的用户请求使得热门网站的网络请求率可能在几秒钟内大规模增加。一旦服务器承受不住这样的高并发请求,由此带来的网络拥塞和延迟会极大地影响用户体验。负载均衡是高可用网络基础架构的关键组件,通过在后端引入一个负载均衡器,将工作负载分布到多个服务器来缓解海量并发请求对服务器造成的巨大压力,提高后端服务器和数据库的性能以及可靠性。而Nginx作为一款高性能的HTTP和反向代理服务器,正越来越多地应用到实践中。文中将分析Nginx服务器负载均衡的体系架构,研究默认的加权轮询算法,并提出一种改进后的动态负载均衡算法,实时收集负载信息,重新计算并分配权值。通过实验测试,对比不同算法下的负载均衡性能,改进后的算法能有效提高服务器集群的性能。     

一种自适应的分布式调度策略

针对集群系统中集中调度存在的单一失效和性能瓶颈问题，本文提出了一种具有自适应特性的分布式集群网络服务器，采用一种新的自适应分布式调度策略，完成对客户请求的动态调度．该策略引入了一种与负载相关的竞争延迟机制，能够根据负载的变化自动选择服务节点，具有很好的自适应性，而且无需节点间通讯，调度的开销小，成本低．另外．该系统通过内核模块实现，做到对客户端和服务端程序透明，其管理配置也相当简单．测试数据表明，该策略具有较好的可扩展性和负载均衡性，实用性强．     

面向Web Service的动态负载均衡设计与实现

负载均衡是分布式系统的资源管理模块,它的主要功能是合理和透明地在服务器之间分配系统负载,以达到系统的综合性能最优。基于中间件的负载均衡技术在整合异构系统、透明访问和扩展能力等方面具有优势。在中间模块上可以灵活实现多种负载均衡算法,来调整和满足不同应用的负载均衡需求,提高系统的扩展性、配置性、健壮性。本文参考分布式系统中的模型,构建了基于Web Service的负载均衡器,实现了动态负载均衡调度策略。为了准确地描述系统的负载,选择CPU利用率、内存利用率、系统响应时间、输入输出流量和进程数作为衡量系统负载的参量;为了避免因监测服务器而加大均衡器的压力,策略中将负载信息采集程序运行在机群内的各服务结点上,当相邻采集周期的负载差值超过标准值后调用均衡器上的Web服务,报告自身的负载状况,使均衡器根据负载信息进行同步操作,更换服务序列。最后通过仿真实验证明本策略在异构Web平台中具有可行性。     

基于AHP的Web集群系统负载均衡算法

利用集群技术构建的服务器组在资源利用率上存在较大差异。为此,提出基于层次分析法(AHP)的集群系统负载均衡算法,建立判断矩阵,得到各项评估指标的单项和综合权重。调度器定时接收真实服务器上的4类参数：网络性能,服务器硬件,服务器软件和网络服务类型。根据调度器收到的每一个连接请求,采用动态反馈算法选择负载最小的服务器响应连接请求。实验结果表明,该算法能减少服务器平均响应时间,有效提高集群系统的响应率。     

Analysis of burstiness monitoring and detection in an adaptive Web system

Due to the heavy tailed pattern of Internet traffic, it is crucial to monitor the incoming arrival rate in a Web system to preserve its performance. In this study, we focus on the arrival rate processing mechanism as part of the design of an adaptive load balancing Web algorithm. The arrival rate is one of the most important metrics to be monitored in a Web site to avoid the possible congestion of Web servers. Six methods are analysed to detect the burstiness of incoming traffic in a Web system. We define six burstiness factors to be individually included in an adaptive load balancing algorithm, which also needs to monitor some Web servers’ parameters continuously, such as the arrival rate at the server or its CPU utilization in order to avoid an unexpected overload situation.We also define adaptive time slot scheduling based on the burstiness factor, which reduces considerably the overhead of the monitoring process by increasing the monitoring frequency when bursty traffic arrives at the system and by decreasing the frequency when no bursts are detected in the arrival rate. Simulation results of the behaviour of the six burstiness factors and adaptive time slot scheduling when sudden changes are detected in the arrival rate are presented and discussed. We have considered a scenario made up of a locally distributed cluster-based Web information system for simulations.     

A new fuzzy-decision based load balancing system for distributed object computing

Distributed object computing systems are widely envisioned to be the desired distributed software development paradigm due to the higher modularity and the capability of handling machine and operating system heterogeneity. Indeed, enabled by the tremendous advancements in processor and networking technologies, complex operations such as object serialization and data marshaling have become very efficient, and thus, distributed object systems are being built for many different applications. However, as the system scales up (e.g., with larger number of server and client objects, and more machines), a judicious load balancing system is required to efficiently distribute the workload (e.g., the queries, messages/objects passing) among the different servers in the system. Unfortunately, in existing distributed object middleware systems, such a load balancing facility does not exist. In this paper, we present the design and implementation of a new dynamic fuzzy-decision-based load balancing system incorporated in a distributed object computing environment. Our proposed approach works by using a fuzzy logic controller which informs a client object to use the most appropriate service such that load balancing among servers is achieved. We have chosen Jini to build our experimental middleware platform, on which our proposed approach as well as other related techniques are implemented and compared. Extensive experiments are conducted to investigate the effectiveness of our fuzzy-decision-based algorithm, which is found to be consistently better than other approaches.