HTTP多路超链接在WebServers中的应用

频繁的WWW访问要求有有效的WebServers组织方式,针对HTTP超链接不能进行负载平衡的缺点,提出了HTTP多路超链接,并用HTTP超链接对HTTP多路超链接进行了模拟,最后将HTTP多路超链接引入WebServers设计。     

Developing a distributed scalable Java component server

We present here approaches for a distributed scalable Java component server. The first one uses a resource broker model, whereby the system is composed of one or several entry point servers, a resource broker and a set of participating servers. The resource broker gives the system its dynamic scalability and load balancing capability by notifying participants and providing information to the entry point servers. An experimental version of the server has been developed. Two other approaches based on Jini and JavaSpace are proposed. An experimental version of the latter one is also compared with the resource broker model.     

一种基于内容的Web集群系统负载均衡算法

1.引言 Internet的普及为人们的工作带来许多方便,人们通过它获取信息或者开展电子商务活动。一个成功的Web站点面临不断增长的访问量和日益复杂的内容处理的挑战。这一切似乎都集中到如何扩充Web站点的处理能力上。早期依靠更高处理性能的服务器系统来解决问题的办法显得笨拙而昂贵。人们开始寻找更加灵活而廉价的技术手段。一些站点采用镜象(mirroring)的方式,在多个服务器上复制相同信息,以不     

Web服务器的安全及负载平衡的研究与实现

随着博鳌网的正式投入使用,博鳌网所承担的信息事务的处理、网站访问量也日益增多,其面临遭遇黑客攻击的风险也越来越大,尤其是代表着单位形象的Web服务,更是需要安全的保障。因此我们研究计算机系统、网络和Web服务器的安全性并构建一个安全可靠的防护体系来保障博鳌网的正常运行。     

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.     

一种分布式网站负载均衡方法

本文介绍了Internet分布式网站负载均衡的基本概念及一种基于负载均衡设备的分布式网站负载均衡方法与组网实例。     

应用负载平衡技术增强Web服务性能

该文简要分析了影响Ｗｅｂ服务性能的因素,对浏览器／服务器结构中Ｗｅｂ服务器负荷过载问题提出解决方法－－采用负载平衡器,并给出了一个负载平衡算法。     

访问Web GIS服务的一种动态负载均衡方法

本文分析了Web GIS的瓶颈问题,引入了基于请求分配器的服务器集群和代理技术,提出了访问Web GIS服务的一种动态负载均衡的方法,从而以较低的成本消除了Web GIS网络瓶颈,提高了Web GIS的数据传输性能。     

Improving the performance for task assignment in distributed server systems by partitioning the large tasks

Task Assignment in distributed server systems focuses on the policy that assigns the tasks reached these systems in order to improve the response time. These tasks, generally, have the property that there is a tiny fraction (about 3%) of the large tasks that makes half (50%) of the total load. However, this property creates additional problems: the large tasks make the load difficult to balance among the servers, and the small tasks will be delayed by the large ones when they are in the same queue. In this paper, we propose a new policy for the Web clusters that we call Partitioning Large Tasks (PLT) and which deals with these problems mostly under a high traffic demand and a high variability of task sizes. PLT partitions each large task into fragments and assigns them to be processed in a parallel way and completing at the same time to improve the mean response time, and separates the small tasks from the large tasks to avoid being delayed. Performance tests show a significantly improvement in performance of PLT over the existing task assignment policies.     

Charlotte: Metacomputing on the Web

Parallel computing on local area networks is generally based on mechanisms that specifically target the properties of the local area network environment. However, these mechanisms do not effectively extend to wide area networks due to issues such as heterogeneity, security, and administrative boundaries. We present a system which enables application programmers to write parallel programs in Java and allows Java-capable browsers to execute parallel tasks. It comprises a virtual machine model which isolates the program from the execution environment, and a runtime system realizing this virtual machine on the Web. Load balancing and fault masking are transparently provided by the runtime system.     

Latency-sensitive hashing for collaborative Web caching

Many geographically distributed proxies are increasingly used for collaborative Web caching to improve performance. In hashing-based collaborative Web caching, the response times can be negatively impacted for those URL requests hashed into geographically distant or overloaded proxies. In this paper, we present and evaluate a latency-sensitive hashing scheme for collaborative Web caching. It takes into account latency delays due to both geographical distances and dynamic load conditions. Each URL request is first hashed into an anchor hash bucket, with each bucket mapping to one of the proxies. Secondly, a number of nearby hash buckets are examined to select the proxy with the smallest latency delay to the browser. Trace-driven simulations are conducted to evaluate the performance of this new latency-sensitive hashing. The results show that (1) with the presence of load imbalance due to skew in request origination or hot-spot references, latency-sensitive hashing effectively balances the load by hashing into geographically distributed proxies for collaborative Web caching, and (2) when the overall system is lightly loaded, latency-sensitive hashing effectively reduces latency delays by directing requests to geographically closer proxies.     

绿色计算与绿色嵌入式系统

绿色计算是一种先进的计算技术,其目的是利用先进的思想、技术和方法来降低 计算系统的能耗,从而减少对人和环境的影响。而今嵌入式系统占整个计算系统的绝大多数,因此,嵌入式系统也需要绿色计算技术,使其能耗降低而不影响其性能。先对绿色计算的研究现状进行综述。然后对绿色嵌入式系统进行定义,并对其内涵进行探讨。最后对绿色嵌入式系统的绿色评价进行了讨论,对绿色嵌入式系统待研究的内容进行了探究。主要创新点在于利用绿色计算思想,提出了绿色嵌入式系统的概念,并对其相关问题进行了研究,指出了绿色嵌入式系统待研究的内容和方向。     

Dynamic file grouping for load balancing in streaming media clustered server systems

A dynamic file grouping strategy is presented to address the load balancing problem in streaming media clustered server systems. This strategy increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves the access hit ratio of cached files in delivery servers to alleviate the limitation of I/O bandwidth of storage node. First, the load balancing problem is formulated as a two layers semi-Markov switching state-space control process. This analytic model captures the behaviors of streaming media clustered server systems accurately, and is with constructional flexibility and scalability. Then, a policy iteration based reinforcement learning algorithm is proposed to optimize the file grouping policy online. By utilizing the features of the event-driven policy, the proposed optimization algorithm is adaptive and with less computational cost. Simulation results demonstrate the effectiveness of the proposed approach. Recommended by Editor Hyun Seok Yang. This work was supported by the National Natural Science Foundation of China under grant Nos. 60774038, 60574065, National 863 HI-TECH Research & Development Plan of China under grant Nos. 2006AA01Z114, 2008AA01A317, Natural Science Foundation of Anhui Province under grant No. 070412063, Graduate Student Innovation Foundation of USTC under grant No. KD2006036, and Science Research Development Foundation of HFUT under grant No. GDBJ2008-045. Qi Jiang received the B.S. degree in Industrial Electrical Automation from Southeast University in 1989 and the Ph.D. degree in Control Science and Engineering from University of Science and Technology of China in 2008. He is currently a Post-doc in USTC. His research interests include optimization and control of stochastic dynamic systems, and performance analysis and optimization of network communication systems. Hong-Sheng Xi received the M.S. degree in Applied Mathematics from University of Science and Technology of China in 1977. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, performance analysis and optimization of network communication systems, robust control, and network security. Bao-Qun Yin received the B.S. degree in Mathematics from Sichuan University in 1985, the M.S. degree in Applied Mathematics and the Ph.D. degree in Pattern Recognition and Intelligent Systems from University of Science and Technology of China in 1993 and 1998, respectively. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, and Markov decision processes.     

一种Web集群系统下的QoS控制策略

本文提出了一种在Web集群环境下的QoS控制策略。集群前端分配器以会话单位来分配访问请求,保证后端服务器间负载的合理均衡分配,同时后端服务器采用基于会话的QoS控制策略,实现对集群系统的服务质量控制。     

Exploiting performance counters to predict and improve energy performance of HPC systems

Hardware monitoring through performance counters is available on almost all modern processors. Although these counters are originally designed for performance tuning, they have also been used for evaluating power consumption. We propose two approaches for modelling and understanding the behaviour of high performance computing (HPC) systems relying on hardware monitoring counters. We evaluate the effectiveness of our system modelling approach considering both optimizing the energy usage of HPC systems and predicting HPC applications’ energy consumption as target objectives. Although hardware monitoring counters are used for modelling the system, other methods–including partial phase recognition and cross platform energy prediction–are used for energy optimization and prediction. Experimental results for energy prediction demonstrate that we can accurately predict the peak energy consumption of an application on a target platform; whereas, results for energy optimization indicate that with no a priori knowledge of workloads sharing the platform we can save up to 24% of the overall HPC system’s energy consumption under benchmarks and real-life workloads.     

Web服务器组的负载均衡方法研究

服务器组是大中型网站建设的重要架构。本文讨论了服务器组的组成模式及其组成结构,针对目前服务器组使用的负载均衡方法所存在的缺陷：未真正考虑到服务器组的当前负载,提出两种新的负载均衡算法,即负载最小优先算法和混合负载均衡算法。实验结果表明,新方法可更有效地均衡服务器组的负载。     

Web search results caching service for structured P2P networks

This paper proposes a two-level P2P caching strategy for Web search queries. The design is suitable for a fully distributed service platform based on managed peer boxes (set-top-box or DSL/cable modem) located at the edge of the network, where both boxes and access bandwidth to those boxes are controlled and managed by an ISP provider. Our solution significantly reduces user query traffic going outside of the ISP provider to get query results from the respective Web search engine. Web users are usually very reactive to worldwide events which cause highly dynamic query traffic patterns leading to load imbalance across peers. Our solution contains a strategy to quickly ease imbalance on peers and spread communication flow among participating peers. Each peer maintains a local result cache used to keep the answers for queries originated in the peer itself and queries for which the peer is responsible for by contacting the Web search engine on-demand. When query traffic is predominantly routed to a few responsible peers our strategy replicates the role of “being responsible for” to neighboring peers so that they can absorb query traffic. This is a fairly slow and adaptive process that we call mid-term load balancing. To achieve a short-term fair distribution of queries we introduce a location cache in each peer which keeps pointers to peers that have already requested the same queries in the recent past. This lets these peers share their query answers with newly requesting peers. This process is fast as these popular queries are usually cached in the first DHT hop of a requesting peer which quickly tends to redistribute load among more and more peers.     

Web 服务器的鲁棒建模和过载控制

给出了一种Web 服务器的建模方法,说明了如何用控制理论管理不可预测的服务器负载。Web 服务器可以被仿真为一个多容器系统。该鲁棒Web 服务器模型适用于未知的负载干扰和不确定的匹配模型。过载控制技术基于自适应允许控制取得时间保证,用一个完整参数变化模型和大的过载来评估模型的性能。     

一种基于预取的集群服务器调度算法

针对集群服务器LARD调度算法只能利用已有缓存的问题,提出一种基于预取的算法Prefetch-LARD,该算法从Web访问日志中挖掘页面之间的转移概率,建立马尔科夫链模型,在调度请求时利用概率关系提前将下一次可能访问的文档从节点磁盘取到本地cache中,提高了请求的缓存命中率;算法还采用了加权的节点超载判断方法,以提高集群节点的负载均衡度,实验表明,在同样的测试环境下,Prefetch-LARD算法比LARD算法的缓存命中率提高26．9％,系统的吞吐量相应提高18．8％．     

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.