Is Fabric Computing the Future of Cloud?

织物计算作为一种新兴概念,正迅速获得关注。它通过将存储、网络和处理等功能紧密集成来提升数据中心效率。本文探讨了从分离到再整合的数据处理方式转变,并分析了这种趋势如何与软件定义的基础设施相结合,进而推动云计算的发展。

 

原文地址:http://cloudcomputing.sys-con.com/node/1755128  感谢作者:GREGOR PETRI

 

云计算还没有站稳脚跟,新的概念又来了!

 

The term fabric computing is gaining rapid popularity, but currently mostly within the hardware community. In fact, according to a recent report, over 50% of attendees at the recent Datacenter Summit had implemented, or are in the process of implementing, fabric computing. Time to take a look at what fabric computing means for software and for (cloud) computing as a whole.

 

Depending on which dictionary you choose, you can find anywhere between two and seven meanings for "fabric." Etymology-wise, it comes from the French fabrique and the Latin fabricare, and the Dutch Fabriek actually means factory. But in an IT context, fabric has little to do with our often used manufacturing or supply chain analogies; instead it actually relates much closer to fabric in its meaning of cloth, a material produced (fabricated) by weaving fibers.

If we check our handy Wikipedia for fabric computing, we get:

Fabric computing or unified computing involves the creation of a computing fabric consisting of interconnected nodes that look like a 'weave' or a 'fabric' when viewed collectively from a distance.[1]

 

Usually this refers to a consolidated high-performance computing system consisting of loosely coupled storage, networking and parallel processing functions linked by high bandwidth interconnects ...

 

 

 

In the context of data centers it means a move from having distinct boxes for handling storage, network and processing towards a fabric where these functions are much more intertwined or even integrated. Most people started to note the move to fabric or unified computing when Cisco started to include servers inside their switches, which they did partly in response to HP including more and more switches in their server deals. Cisco's UCS (Unified Computing System), and its bigger sibling, VCE, are the first hardware examples of this trend (although inside the box you can still distinguish the original components).

One reason to move to such a fabric design is that by moving data, network and compute closer together (integrating them) you can improve performance. Juniper's recent QFabric architecture announcement is another similar example. But, the idea of closer integration of data, processing, and communication is actually much older. In some respects, we may even conclude IT is coming full circle with this trend.

Let me explain.

Many years ago I spoke to Professor Scheer, founder of IDS Scheer and a pioneer in the field of Business Process Management (BPM). (Disclosure: years later IDS Scheer became part of my former employer: Software AG.) He spoke about how - in the old days of IT - data and logic were seen as one. Literally! If - while walking with your stack of punch cards to the computer room (back then it was a computer the size of a room, not a room with a computer in it) - you dropped your stack of punch cards, both data and logic would be in one pile on the floor. You would spend the rest of your afternoon sorting them again. There was just one stack: first the processing/algorithm logic, and then the data. Scheer's point was that just like we figured out after a while that data did not belong there and we moved it to its own place (typically a relational database), we should now separate the process flow instructions from the algorithms and move these to a workflow process engine (preferably of course his BPM engine). All valid and true - at that time.

 

But not long after, Object Oriented programming became the norm, and we started to move data back with the logic that understood how to handle that data, and treat them as objects. This of course created a new issue of having these objects perform in an even more remotely acceptable way, as we used relational databases to store or persist the data inside these objects. You could compare this to disassembling your car every night into its original pieces in order to put it in your garage. Over the years the industry figured out how to do this better,in part by creating new databases which design-wise looked remarkably similar to the (hierarchical) databases we used back in the day of punch cards.

 

And now , under the new shiny name of fabric computing we are moving all these processes back in the same physical box.

 

But this is not the whole story -- there is another revolution happening. As an industry we are moving from using dedicated hardware for specialized tasks to generic hardware with specialized software instead. For example, you might use a software virtualization layer to simply emulate a certain piece of specific hardware.

 

Or, look at a firewall: traditionally it was a piece of dedicated hardware built to do one thing (keeping non-allowed traffic out). Today, most firewalls are software-based. We use a generic processor to take care of that task. And we're seeing this trend unfold with more equipment in the data center. Even switches, load balancers and network-attached storage are becoming software-based (virtual appliance seems to be the preferred marketing buzzword for this trend).

 

Using software is more efficient than having loads of dedicated hardware, and we can't ignore the fact that software, because of its completely different economic and management characteristics, has numerous inherent advantages over hardware. For example, you can copy, change, delete and distribute software, all remotely, without having to leave your seat, and even do automatically. You'd need some pretty advanced robots to do that with hardware (if it could be done today).

 

So how do these two trends relate to cloud computing?

By combining the idea of moving stuff that needs to work together closer together (the idea of fabric) and the idea of doing that by using software instead of hardware (which gives us the economics and manageability of software) we can create higher performance, lower cost and easier to manage clouds.

 

Virtualization has been on a similar path. First we virtualized servers, then storage and networking, but all remained in their separate silos. Now we are virtualizing all of it in the same "fabric." This means that managing the entire stack gets simpler, with one tool to define it, make it work and monitor it. And that's something that should make any IT pro smile.

 

In my next post, I'll share my thoughts on why I think this approach has the power to change IT as we know it, based on some of my own epiphanies.

【论文复现】一种基于价格弹性矩阵的居民峰谷分时电价激励策略【需求响应】(Matlab代码实现)内容概要:本文介绍了一种基于价格弹性矩阵的居民峰谷分时电价激励策略,旨在通过需求响应机制优化电力系统的负荷分布。该研究利用Matlab进行代码实现,构建了居民用电行为与电价变动之间的价格弹性模型,通过分析不同时间段电价调整对用户用电习惯的影响,设计合理的峰谷电价方案,引导用户错峰用电,从而实现电网负荷的削峰填谷,提升电力系统运行效率与稳定性。文中详细阐述了价格弹性矩阵的构建方法、优化目标函数的设计以及求解算法的实现过程,并通过仿真验证了所提策略的有效性。; 适合人群:具备一定电力系统基础知识和Matlab编程能力,从事需求响应、电价机制研究或智能电网优化等相关领域的科研人员及研究生。; 使用场景及目标:①研究居民用电行为对电价变化的响应特性;②设计并仿真基于价格弹性矩阵的峰谷分时电价激励策略;③实现需求响应下的电力负荷优化调度;④为电力公司制定科学合理的电价政策提供理论支持和技术工具。; 阅读建议:建议读者结合提供的Matlab代码进行实践操作,深入理解价格弹性建模与优化求解过程,同时可参考文中方法拓展至其他需求响应场景,如工业用户、商业楼宇等,进一步提升研究的广度与深度。
针对TC275微控制器平台,基于AUTOSAR标准的引导加载程序实现方案 本方案详细阐述了一种专为英飞凌TC275系列微控制器设计的引导加载系统。该系统严格遵循汽车开放系统架构(AUTOSAR)规范进行开发,旨在实现可靠的应用程序刷写与启动管理功能。 核心设计严格遵循AUTOSAR分层软件架构。基础软件模块(BSW)的配置与管理完全符合标准要求,确保了与不同AUTOSAR兼容工具链及软件组件的无缝集成。引导加载程序本身作为独立的软件实体,实现了与上层应用软件的完全解耦,其功能涵盖启动阶段的硬件初始化、完整性校验、程序跳转逻辑以及通过指定通信接口(如CAN或以太网)接收和验证新软件数据包。 在具体实现层面,工程代码重点处理了TC275芯片特有的多核架构与内存映射机制。代码包含了对所有必要外设驱动(如Flash存储器驱动、通信控制器驱动)的初始化与抽象层封装,并设计了严谨的故障安全机制与回滚策略,以确保在软件更新过程中出现意外中断时,系统能够恢复到已知的稳定状态。整个引导流程的设计充分考虑了时序确定性、资源占用优化以及功能安全相关需求,为汽车电子控制单元的固件维护与升级提供了符合行业标准的底层支持。 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!
Journal of Cloud Computing: Advances, Systems and Applications 是一本专注于云计算领域的高质量学术期刊,涵盖了云计算的理论研究、系统实现和实际应用等多个方面。该期刊的官方网站为 [https://journalofcloudcomputing.springeropen.com/](https://journalofcloudcomputing.springeropen.com/),由 SpringerOpen 出版社负责出版。该期刊采用开放获取(Open Access)模式,所有文章均可免费阅读和下载。 该期刊的投稿范围包括但不限于以下主题: - 云计算架构与模型 - 虚拟化技术 - 云资源管理与调度 - 云安全与隐私保护 - 云存储与数据管理 - 分布式云与边缘计算 - 云服务质量(QoS)与性能优化 - 云应用案例与经验分享 - 云与大数据的融合 - 移动云计算与物联网(IoT)集成 [^1] 在该期刊上发表的论文通常包括原创研究论文(Research Articles)、综述论文(Review Articles)以及短篇通讯(Short Communications)。投稿者需通过其在线投稿系统(Editorial Manager)提交稿件,所有稿件均经过严格的同行评审流程。 例如,该期刊曾发表过以下具有代表性的论文: - **"A survey on virtual machine migration in cloud computing and its challenges"** 该综述论文系统性地总结了云计算中虚拟机迁移技术的研究进展,并分析了不同迁移策略在性能、能耗、安全等方面的优劣。 - **"Energy-efficient resource allocation in cloud computing: A survey"** 本文探讨了云计算环境下的节能资源分配策略,包括虚拟机放置、负载均衡、动态资源调度等关键技术。 - **"Security and privacy issues in cloud computing: A comprehensive survey"** 本研究综述了当前云计算中存在的主要安全与隐私问题,并对现有的防护机制、加密技术与访问控制方法进行了比较分析。 对于希望了解该期刊最新研究成果的读者,可以通过其官网访问最新发表的文章列表。此外,Google Scholar、Scopus、Web of Science 等学术数据库也收录了该期刊的全部论文内容,便于检索和引用。 ```python # 示例:使用 Python 请求 Journal of Cloud Computing 的 RSS Feed 获取最新文章信息 import feedparser rss_url = 'https://journalofcloudcomputing.springeropen.com/rss' feed = feedparser.parse(rss_url) for entry in feed.entries[:5]: # 获取最近5篇文章 print(f"Title: {entry.title}") print(f"Link: {entry.link}") print(f"Published: {entry.published}") print('-' * 40) ```
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