Single IP Address Cluster

本文介绍了一种称为SAPS的单地址协议栈技术,该技术能够使计算机集群从IP网络角度看作单一系统。通过将集群视为拥有单一IP地址的实体,客户端可以如同面对单一计算机一样进行访问。这种设计适用于大规模Web服务器或作为网格节点的PC集群。

Single IP Address Cluster

We are investigating a new network protocol stack for a single system image cluster. It is called SAPS (Single Address Protocol Stack). The main objective of SAPS is to make a cluster of computers a single system from an IP network point of view. With SAPS, a cluster has a single IP address. Client computers access the cluster using this IP address as if it were a single computer. The single system image cluster is used for large-scale web servers, or PC clusters used as a node of a grid because the single system image makes it easier to manage the cluster or to build an application for the cluster.

 

Figure 1. Single IP Address Cluster

 

Design

In order to realize a single IP address on physically distributed computers, a computer that handles all the network I/O is introduced. This is called the I/O server. The other nodes are called application nodes. They provide the socket interface to applications. The overall design of SAPS is shown in Figure 1.

The I/O server receives packets from the Internet. TCP protocol handling is performed on this computer. The received data is forwarded to an application node on which the process responsible for that data is running.

Outgoing messages are forwarded from an application node to the I/O server. In the server, TCP packets are constructed and sent to the Internet. Control messages are also transferred between the I/O server and application nodes. The control messages consist of the notification of the arrival of a new connection, or a port number to listen on.

For the cluster network that forwards the data and control messages, a reliable high performance interface is assumed such as Myrinet or Infiniband.

 

 

 

Socket Migration

In the traditional cluster, it is impossible to move a process with IP sockets from one node to another because two nodes have different IP addresses. By using SAPS, IP sockets may be migrated between two application nodes because they work on the same IP address.

While a process is moving the node, the I/O server stops forwarding received data and buffers it on the server. After the migration is completed, the buffered data is sent to the migrated node. The I/O server continues to perform the protocol handling during the migration. Thus, TCP connections need not be closed to migrate the process.

 

Figure 3. Socket Migration

 

Implementation

SAPS is currently implemented as a kernel module of Linux kernel 2.6.13. As a cluster network, the Myrinet network and the PM/Myrinet[2] communication library are used. On the I/O server, the original implementation of the TCP/IP protocol stack is extended so that communication is initiated by the arrival of the data from the cluster network, instead of system calls. The I/O server converts the protocol between TCP/IP and the protocol of the cluster network. This conversion is realized by rewriting the header of each packet. Thus, data copying does not happen on the I/O server. On the application nodes, we made a new implementation of the socket interface. This new socket provides fully compatible interfaces to the applications. Thus, no modification is required to the existing applications. No kernel patch is required on either the I/O server or the application nodes.

 

Performance

All the measurements are done using computers with the Opteron or Xeon processor and a PCI-X bus. In order to compare the performance of SAPS with that of the Virtual Server[3], the performance of the network using Network Address Translation (NAT) is also measured..

The user level point-to-point performance is shown in Table 1 and Figure 3. These results show SAPS performs better than NAT.

 

      Table 1. Round trip time    (µs)

 

Min.

Max.

Avg.

SAPS

165

243

217.6

NAT

210

334

255.6

 

Figure 4. Point-to-Point Bandwidth

 

 

 

Using a 3-node (plus one I/O server) cluster and three clients, the performance of SAPS is measured with multiple streams. In order to emulate the Internet, a 5ms delay is added in the route as shown in Figure 6.

 

Figure.6 Multiple Stream

 

 

For the evaluation with multiple streams, three application nodes send data to each client at the same time. The throughput of each stream is measured at the delay router. As shown in Figure 5, three streams share the available bandwidth equally in SAPS while unfair sharing is observed in NAT.

 

Figure 5. Multiple Stream Performance

 
 

 

 

Related Work

Kerrighed[4] is a research project to develop a single system image OS for clusters. Its Dynamic Streams supports the migration of sockets[1] but is not designed to migrate processes that are communicating with processes running outside the cluster.

 Virtual Server[3] provides the single system image from the point of view of computers outside the cluster. Virtual Server does not provide the single system image inside the cluster and it does not enable the migration of communicating process.

Work in Progress

  We have realized the single IP address cluster and socket migration with a good performance. By adding features such as single authentication and inter-node IPC, we intend to develop a single system image OS.

 

References

1.     Pascal Gallard and Christine Morin.  Dynamic Streams For Efficient Communications between Migrating Processes in a Cluster . Parallel Processing Letters, 13(4)

2.  Toshiyuki Takahashi, Shinji Sumimoto, Atsushi Hori, Hiroshi Harada, and Yutaka Ishikawa. PM2:High performance communication middleware for heterogeneous network environments. In Proceedings of the IEEE/ACM SC2000 Conference, 2000.

3.        Wensong Zhang. Linux Virtual Servers for Scalable Network Services. Linux Symposium, 2000.

4.        http://www.kerrighed.org

基于径向基函数神经网络RBFNN的自适应滑模控制学习(Matlab代码实现)内容概要:本文介绍了基于径向基函数神经网络(RBFNN)的自适应滑模控制方法,并提供了相应的Matlab代码实现。该方法结合了RBF神经网络的非线性逼近能力和滑模控制的强鲁棒性,用于解决复杂系统的控制问题,尤其适用于存在不确定性和外部干扰的动态系统。文中详细阐述了控制算法的设计思路、RBFNN的结构与权重更新机制、滑模面的构建以及自适应律的推导过程,并通过Matlab仿真验证了所提方法的有效性和稳定性。此外,文档还列举了大量相关的科研方向和技术应用,涵盖智能优化算法、机器学习、电力系统、路径规划等多个领域,展示了该技术的广泛应用前景。; 适合人群:具备一定自动控制理论基础和Matlab编程能力的研究生、科研人员及工程技术人员,特别是从事智能控制、非线性系统控制及相关领域的研究人员; 使用场景及目标:①学习和掌握RBF神经网络与滑模控制相结合的自适应控制策略设计方法;②应用于电机控制、机器人轨迹跟踪、电力电子系统等存在模型不确定性或外界扰动的实际控制系统中,提升控制精度与鲁棒性; 阅读建议:建议读者结合提供的Matlab代码进行仿真实践,深入理解算法实现细节,同时可参考文中提及的相关技术方向拓展研究思路,注重理论分析与仿真验证相结合。
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值