Perlbal is our Perl-based reverse proxy load balancer and web server

Perlbal是一款基于Perl的反向代理负载均衡器及Web服务器。它支持HTTP负载均衡、Web服务等功能,并具备高度可配置性,无需重启即可进行配置更改。Perlbal能够维护与后端服务器的持久连接,并提供智能负载均衡策略。
原贴:http://www.ourlinux.net/date/2007/03/

Perlbal

Perlbal is our Perl-based reverse proxy load balancer and web server.

Overview

Perlbal is a single-threaded event-based server supporting HTTP load balancing, web serving, and a mix of the two (see below).

One of the defining things about Perlbal is that almost everything can be configured or reconfigured on the fly without needing to restart the software. A basic configuration file containing a management port enables you to easily perform operations on a running instance of Perlbal.

Here is a basic list of the personalities and features that Perlbal implements at this time.

Role: Web Server

  • Listen on a port, share from a directory
  • Directory indexing
  • Byte range support (clients can resume downloads)
  • Can have directory index requests fall back to index file list
    • I.e., requests for /foo/ go to /foo/index.html instead
    • Multiple index files supported, tries one at a time until it finds one
  • Persistent client connections (configurable)
  • Almost all1 disk operations are done asynchronously as to not stall the event loop
  • Configurable support for storing files (PUT, DELETE support)

1 Almost. When you enable PUT support, the close() operation is blocking. However, it’s generally pretty fast (we’ve had no problems). Also, directory indexing is a synchronous operation.

Role: Reverse Proxy

  • Maintains pool of connected backend connections to reduce turnover
  • Gets list of nodes either from asynchronously monitored node file, or from in-server pool objects which you can add/remove nodes from using the management interface.
  • Intelligent load balancing based on what backend connections are free for a new request. No unreliable “weighting” numbers required.
  • Can verify (using a quick OPTIONS request) that a backend connection is talking to a webserver and not just the kernel’s listen queue before sending client requests at it. Lower latency for the client.
  • Has a high priority queue for sending requests through to backends quickly
    • Uses cookies to determine if a request should go to fast queue (configurable)
    • Highpri (high priority) plugin supports making requests high priority by URI or Host
    • Can specify a relief level to let low priority requests through to prevent starvation
  • Can allow X-Forwarded-For (and similar) headers from client based on client IP
  • Configurable header management before sending request to backend
  • Internal redirection to file or URL(s)
    • Big one for us; a backend can instruct Perlbal to fetch the user’s data from a completely separate server and port and URL, 100% transparent to the user
    • Can actually give Perlbal a list of URLs to try. Perlbal will find one that’s alive. Again, the end user sees no redirects happening.
    • Can also redirect to a file, which Perlbal will serve non-blocking. See webserver mode above.
  • Persistent client connections (configurable)

Statistics and Monitoring

  • CPU usage (user, system)
  • Total requests served across all services
  • Requests service by individual backends
  • Perlbal uptime
  • All connected sockets (and tons of info about each)
  • Outstanding connections to backends
  • Backends that have recently failed verification
  • Pending backend connections by service
  • Total of all socket states by socket type
  • Size (in seconds and number of connections) of all queues
  • State of reproxy engine (queued requests, outstanding requests, backends)
  • Loaded plugins per service

(All statistics are in machine readable form, easy to parse and write scripts that check on the status of Perlbal!)

Plugins (Extensibility)

Perlbal supports the concept of having per-service (and global) plugins that can override many parts of request handling and behavior. We have written custom plugins that send new headers to the backends, promote requests to the fast queue, maintain more detailed statistics, do image header manipulation, and more…

For more information on how plugins work, see the plugins directory in the distribution. They’re fairly self-explanatory.

Much more documentation needs to happen…

具体的安装方法可以见这里: http://wiki.ourlinux.net/pmwiki.php?n=Main.Perlbal

提供了基于BP(Back Propagation)神经网络结合PID(比例-积分-微分)控制策略的Simulink仿真模型。该模型旨在实现对杨艺所著论文《基于S函数的BP神经网络PID控制器及Simulink仿真》中的理论进行实践验证。在Matlab 2016b环境下开发,经过测试,确保能够正常运行,适合学习和研究神经网络在控制系统中的应用。 特点 集成BP神经网络:模型中集成了BP神经网络用于提升PID控制器的性能,使之能更好地适应复杂控制环境。 PID控制优化:利用神经网络的自学习能力,对传统的PID控制算法进行了智能调整,提高控制精度和稳定性。 S函数应用:展示了如何在Simulink中通过S函数嵌入MATLAB代码,实现BP神经网络的定制化逻辑。 兼容性说明:虽然开发于Matlab 2016b,但理论上兼容后续版本,可能会需要调整少量配置以适配不同版本的Matlab。 使用指南 环境要求:确保你的电脑上安装有Matlab 2016b或更高版本。 模型加载: 下载本仓库到本地。 在Matlab中打开.slx文件。 运行仿真: 调整模型参数前,请先熟悉各模块功能和输入输出设置。 运行整个模型,观察控制效果。 参数调整: 用户可以自由调节神经网络的层数、节点数以及PID控制器的参数,探索不同的控制性能。 学习和修改: 通过阅读模型中的注释和查阅相关文献,加深对BP神经网络与PID控制结合的理解。 如需修改S函数内的MATLAB代码,建议有一定的MATLAB编程基础。
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