11 Top Open-source Resources for Cloud Computing

本文介绍了11种顶级的开源云资源,包括应用、服务、教育资料等,旨在帮助企业降低成本并提高灵活性。涵盖Eucalyptus、Red Hat的云解决方案、TrafficServer、Cloudera、Puppet等。

11 Top Open-source Resources for Cloud Computing

http://gigaom.com/2009/11/06/10-top-open-source-resources-for-cloud-computing/

 

Open-source software has been on the rise at many businesses during the extended economic downturn, and one of the areas where it is starting to offer companies a lot of flexibility and cost savings is in cloud computing. Cloud deployments can save money, free businesses from vendor lock-ins that could really sting over time, and offer flexible ways to combine public and private applications. The following are 11 top open-source cloud applications, services, educational resources, support options, general items of interest, and more.

Eucalyptus . Ostatic broke the news about UC Santa Barbara’s open-source cloud project last year. Released as an open-source (under a FreeBSD-style license) infrastructure for cloud computing on clusters that duplicates the functionality of Amazon’s EC2, Eucalyptus directly uses the Amazon command-line tools. Startup Eucalyptus Systems was launched this year with venture funding , and the staff includes original architects from the Eucalyptus project. The company recently released its first major update to the software framework , which is also powering the cloud computing features in the new version of Ubuntu Linux.

Red Hat’s Cloud . Linux-focused open-source player Red Hat has been rapidly expanding its focus on cloud computing. At the end of July, Red Hat held its Open Source Cloud Computing Forum, which included a large number of presentations from movers and shakers focused on open-source cloud initiatives. You can find free webcasts for all the presentations here . The speakers include Rich Wolski (CTO of Eucalyptus Systems), Brian Stevens (CTO of Red Hat), and Mike Olson (CEO of Cloudera). Stevens’ webcast can bring you up to speed on Red Hat’s cloud strategy. Novell is also an open source-focused company that is increasingly focused on cloud computing, and you can read about its strategy here .

Traffic Server . Yahoo this week moved its open-source cloud computing initiatives up a notch with the donation of its Traffic Server product to the Apache Software Foundation. Traffic Server is used in-house at Yahoo to manage its own traffic, and it enables session management, authentication, configuration management, load balancing, and routing for entire cloud computing software stacks. Acting as an overlay to raw cloud computing services, Traffic Server allows IT administrators to allocate resources , including handling thousands of virtualized services concurrently.

Cloudera . The open-source Hadoop software framework is increasingly used in cloud computing deployments due to its flexibility with cluster-based, data-intensive queries and other tasks. It’s overseen by the Apache Software Foundation, and Yahoo has its own time-tested Hadoop distribution . Cloudera is a promising startup focused on providing commercial support for Hadoop. You can read much more about Cloudera here .

Puppet . Virtual servers are on the rise in cloud computing deployments, and Reductive Labs’ open-source software, built upon the legacy of the Cfengine system , is hugely respected by many system administrators for managing them . You can use it to manage large numbers of systems or virtual machines through automated routines, without having to do a lot of complex scripting.

Enomaly . The company’s Elastic Computing Platform (ECP) has its roots in widely used Enomalism open-source provisioning and management software, designed to take much of the complexity out of starting a cloud infrastructure . ECP is a programmable virtual cloud computing infrastructure for small, medium and large businesses, and you can read much more about it here .

Joyent . In January of this year, Joyent purchased Reasonably Smart, a fledgling open-source cloud startup based on JavaScript and Git. Joyent’s cloud hosting infrastructure and cloud management software incorporate many open-source tools for public and private clouds.  The company can also help you optimize a speedy implementation of the open-source MySQL database for cloud use.

Zoho . Many people use Zoho’s huge suite of free, online applications, which is competitive with Google Docs. What lots of folks don’t realize, though, is that Zoho’s core is completely open source — a shining example of how SaaS solutions can work in harmony with open source. You can find many details on how Zoho deploys open-source tools in this interview .

Globus Nimbus . This open-source toolkit allows businesses to turn clusters into Infrastructure-as-a-Service (IaaS) clouds. The Amazon EC2 interface is carried over, but is not the only interface you can choose.

Reservoir . This is the main European research initiative on virtualized infrastructures and cloud computing. It’s a far-reaching project targeted to develop open-source technology for cloud computing, and help businesses avoid vendor lock-in.

OpenNebula . The OpenNebula VM Manager is a core component of Reservoir. It’s an open-source answer to the many virtual machine management offerings from proprietary players, and interfaces easily with cloud infrastructure tools and services. “OpenNebula is an open-source virtual infrastructure engine that enables the dynamic deployment and re-placement of virtual machines on a pool of physical resources,” according to project leads.

It’s good to see open-source tools and resources competing in the cloud computing space. The end result should be more flexibility for organizations that want to customize their approaches. Open-source cloud offerings also have the potential to keep pricing for all competitive services on a level playing field.

同步定位与地图构建(SLAM)技术为移动机器人或自主载具在未知空间中的导航提供了核心支撑。借助该技术,机器人能够在探索过程中实时构建环境地图并确定自身位置。典型的SLAM流程涵盖传感器数据采集、数据处理、状态估计及地图生成等环节,其核心挑战在于有效处理定位与环境建模中的各类不确定性。 Matlab作为工程计算与数据可视化领域广泛应用的数学软件,具备丰富的内置函数与专用工具箱,尤其适用于算法开发与仿真验证。在SLAM研究方面,Matlab可用于模拟传感器输出、实现定位建图算法,并进行系统性能评估。其仿真环境能显著降低实验成本,加速算法开发与验证周期。 本次“SLAM-基于Matlab的同步定位与建图仿真实践项目”通过Matlab平台完整再现了SLAM的关键流程,包括数据采集、滤波估计、特征提取、数据关联与地图更新等核心模块。该项目不仅呈现了SLAM技术的实际应用场景,更为机器人导航与自主移动领域的研究人员提供了系统的实践参考。 项目涉及的核心技术要点主要包括:传感器模型(如激光雷达与视觉传感器)的建立与应用、特征匹配与数据关联方法、滤波器设计(如扩展卡尔曼滤波与粒子滤波)、图优化框架(如GTSAM与Ceres Solver)以及路径规划与避障策略。通过项目实践,参与者可深入掌握SLAM算法的实现原理,并提升相关算法的设计与调试能力。 该项目同时注重理论向工程实践的转化,为机器人技术领域的学习者提供了宝贵的实操经验。Matlab仿真环境将复杂的技术问题可视化与可操作化,显著降低了学习门槛,提升了学习效率与质量。 实践过程中,学习者将直面SLAM技术在实际应用中遇到的典型问题,包括传感器误差补偿、动态环境下的建图定位挑战以及计算资源优化等。这些问题的解决对推动SLAM技术的产业化应用具有重要价值。 SLAM技术在工业自动化、服务机器人、自动驾驶及无人机等领域的应用前景广阔。掌握该项技术不仅有助于提升个人专业能力,也为相关行业的技术发展提供了重要支撑。随着技术进步与应用场景的持续拓展,SLAM技术的重要性将日益凸显。 本实践项目作为综合性学习资源,为机器人技术领域的专业人员提供了深入研习SLAM技术的实践平台。通过Matlab这一高效工具,参与者能够直观理解SLAM的实现过程,掌握关键算法,并将理论知识系统应用于实际工程问题的解决之中。 资源来源于网络分享,仅用于学习交流使用,请勿用于商业,如有侵权请联系我删除!
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