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5g 為什麼需要邊緣雲_5g将雲的力量帶到了邊緣 背景 (Background) 遷移到雲端 (Moving to the Cloud) 5G物聯網的局限性 (Limitations of 5G Powered IoT) 物聯網公司在5G革命期間取得成功的政策 (Strategies for IoT Companies to Succeed During the 5G Revolution)

5g 為什麼需要邊緣雲

by Peter McHale, Summer Associate, Darling Ventures

作者:Darling Ventures夏季合夥人Peter McHale

Big data management, SAAS, predictive analytics, and AI — these are just a few industries enabled by cloud computing. So much of the recent innovation we see in software has been unlocked by the cloud, you would be forgiven for thinking that everything is running on AWS or on another server farm. IoT, however, is a huge market of game-changing technology that has not been able to partake in cloud computing’s accessible economics and powerful computing capabilities. IoT applications often need an immediate reaction to what they sense, generate massive amounts of data to be processed, and have unique security constraints.

大資料管理,SAAS,預測分析和人工智能-這些隻是雲計算支援的少數幾個行業。 我們在軟體中看到的許多最新創新已經被雲解鎖,您認為一切都在AWS或另一個伺服器場上運作就可以了。 但是,物聯網是一個巨大的改變遊戲規則的技術市場,它無法參與雲計算的可通路經濟性和強大的計算功能。 物聯網應用通常需要對其感覺立即做出React,生成大量要處理的資料,并具有獨特的安全性限制。

5G is about to change that. With its ultra-low latency, ability to cheaply send large amounts of data, and improved security, 5G will empower many IoT devices with the computational power of the cloud. When 5G powered IoT is able to utilize the capable AI algorithms that live in the cloud, we will see an IoT explosion of possibilities become reality. This shift offers great opportunity for companies working in the IoT space but also warrants a reexamination of their strategy and value proposition.

5G即将改變這種狀況。 5G具有超低的延遲,廉價地發送大量資料的能力以及更高的安全性,将使許多物聯網裝置具有雲計算能力。 當支援5G的IoT能夠利用雲中強大的AI算法時,我們将看到IoT爆炸的可能性變為現實。 這一轉變為物聯網領域的公司提供了巨大的機會,但也需要重新審視其戰略和價值主張。

背景 (Background)

In the early 2000s, multiple startups, such as Marc Andreessen’s Opsware, popped up with a cloud computing product before most understood what the cloud was. Large companies such as Amazon and Microsoft later came out with offerings like AWS and Azure that made cloud computing as widespread as it is today. Outsourcing cloud computing to offerings such as AWS was attractive to companies for a number of reasons: 1) companies were able to have cheap upfront costs without having to buy expensive server hardware, 2) companies gained unprecedented reliability by shifting the responsibilities of maintaining servers to outside vendors, thus maximizing uptime and 3) companies were able to manage diverse web-traffic rates by paying as they went with unlimited accessibility to more computing resources. So why hasn’t IoT participated in these huge benefits?

在2000年代初期,馬克·安德森(Marc Andreessen)的Opsware等多家初創公司突然湧現出了雲計算産品,這才讓大多數人了解雲是什麼。 像亞馬遜和微軟這樣的大公司後來推出了像AWS和Azure這樣的産品,它們使雲計算像今天一樣廣泛地傳播。 将雲計算外包到AWS之類的産品對公司具有吸引力,其原因有很多:1)公司無需購買昂貴的伺服器硬體即可獲得便宜的前期成本; 2)公司通過将維護伺服器的職責轉移到外部供應商,進而最大程度地延長了正常運作時間; 3)公司能夠通過無限制通路更多計算資源的方式付費來管理各種網絡流量費率。 那麼,為什麼物聯網沒有參與這些巨大的利益呢?

IoT applications have been limited by three constraints that have kept them using computational and data storage resources at “the edge”, or close to where the data is created and the application is utilized. Many of these applications have unique security requirements that prevent them from sending their data to an external server. Other applications are constrained by not being able to cheaply send large amounts of data through the internet to a server. Finally, some applications need ultra-low latency to react quickly to data or input at the edge. 5G is about to meet these needs for many IoT applications and allow them to reap the benefits of the cloud. Now let’s explore this 5G IoT revolution.

物聯網應用受到三個限制的限制,這使它們無法在“邊緣”或接近建立資料和使用應用的位置使用計算和資料存儲資源。 這些應用程式中的許多應用程式都具有獨特的安全性要求,以防止它們将資料發送到外部伺服器。 其他應用程式由于無法通過Internet廉價地将大量資料發送到伺服器而受到限制。 最後,某些應用程式需要極低的延遲才能對邊緣的資料或輸入做出快速React。 5G即将滿足許多物聯網應用程式的這些需求,并使它們能夠從雲中受益。 現在讓我們探索5G IoT革命。

遷移到雲端 (Moving to the Cloud)

5g 為什麼需要邊緣雲_5g将雲的力量帶到了邊緣 背景 (Background) 遷移到雲端 (Moving to the Cloud) 5G物聯網的局限性 (Limitations of 5G Powered IoT) 物聯網公司在5G革命期間取得成功的政策 (Strategies for IoT Companies to Succeed During the 5G Revolution)

Alexandre Debiève on AlexandreDebiève在Unsplash上 Unsplash 拍攝

One area that is receiving plenty of attention from 5G media is VR, and for good reason. Currently, VR means buying high-priced hardware for an experience you likely aren’t using all the time because there isn’t a fast-enough means of receiving data that isn’t within a few feet of you. There’s already talk about using ultra fast latency to move this processing to the cloud, and bring about pay-as-you-go virtual reality as a service. 5G will bring this reality closer, but before we see that total paradigm shift, 5G is enabling VR to utilize cloud resources. BAD VR is an early such example, focusing on how VR can be used for visualizing data analytics. Imagine a world in which emergency phone operators update a back-end that lives in the cloud with data on a current emergency, while first responders wear augmented reality headsets that help them visualize all the data about the current incident, as well as any medical guidance to support their efforts once they arrive. All of this data would stream reliably and instantly via 5G when every second counts . This is the world that BAD VR is working to create.

VR受到5G媒體的廣泛關注,這是有充分理由的。 目前,VR意味着購買昂貴的硬體,以獲得您可能不會一直使用的體驗,因為沒有足夠快的方法來接收不在您幾英尺之内的資料。 已經有關于使用超快速延遲将處理轉移到雲中并帶來即付即用的虛拟現實即服務的讨論。 5G将使這一現實更加接近,但是在我們看到整體模式轉變之前,5G使VR能夠利用雲資源。 BAD VR就是這樣的早期例子,專注于如何将VR用于可視化資料分析。 想象一下這樣一個世界:緊急電話營運商使用目前緊急情況的資料來更新駐留在雲中的後端,而第一響應者戴着增強現實耳機,以幫助他們可視化有關目前事件的所有資料以及任何醫療指導一旦他們到達就支援他們的努力。 每秒鐘都可以通過5G可靠,即時地傳輸所有這些資料。 這就是BAD VR正在努力創造的世界。

While BAD VR is working to equip first responders navigating a city, others are focused on the city itself. Cities will become smarter and smarter via lightweight and cheap sensing hardware scattered around them. This hardware will communicate with the cloud, hosting large-scale optimizations and coordinating thousands of tasks using powerful AI. AI will then communicate with vehicles and pedestrians to create some remarkable mobility efficiencies. Haas Alert is an early player in this space. Their product enables first responders to communicate information to a “safety cloud” that then alerts motorists immediately of an accident so that they can slow down well in advance of seeing it. While there is some manual data input happening here, we will see more and more of these applications being automated.

雖然BAD VR緻力于為急救人員配備導航城市的裝置,但其他人則專注于城市本身。 通過散布在周圍的輕巧廉價的傳感硬體,城市将變得越來越智能。 該硬體将與雲通信,托管大型優化并使用強大的AI協調數千個任務。 然後,AI将與車輛和行人通信,以創造出顯着的移動效率。 Haas Alert是該領域的早期參與者。 他們的産品使急救人員能夠将資訊傳達到“安全雲”,然後立即向駕駛員發出事故警報,以便他們能夠在看到事故之前放慢速度。 盡管這裡發生了一些手動資料輸入,但我們将看到越來越多的這些應用程式是自動化的。

Navilens is another early contender in the smart city space. Their app scans QR-like codes placed throughout a city to help people with visual impairments navigate through the city, or to help unimpaired pedestrians gain access to navigational information that is relevant to their exact location. This allows people to use the same technology outdoors or indoors (where GPS doesn’t work so well), potentially even while using a subway. They’re currently limited by the number of images scanned, however 5G’s data rates will greatly lift that constraint with access to cloud compute resources and will enable more seamless and exact navigational information.

Navilens是智慧城市領域的另一位早期競争者。 他們的應用程式會掃描遍布整個城市的類似QR碼,以幫助有視覺障礙的人在整個城市中導航,或幫助無障礙的行人獲得與其确切位置相關的導航資訊。 這樣一來,即使在使用地鐵的情況下,人們也可以在室外或室内(GPS無法正常工作)使用相同的技術。 它們目前受到掃描圖像數量的限制,但是5G的資料速率将極大地限制對雲計算資源的通路限制,并将啟用更加無縫和準确的導航資訊。

Smart manufacturing plants need quick responses to failing machinery or process failures. When 5G brings increased security and ultra-low latency, plants can send non-sensitive data to platforms and resource-intensive AI living in the cloud to perform analysis and then immediately respond at the plant. Petasense is a great example of this. A plant places a Petasense device on a machine that then sends accelerometer data to a platform in the cloud that uses AI. With the combined compute power of the cloud and the data from the IoT sensor in the plant, an AI can detect a failing machine and send a signal to the plant to shut down and schedule maintenance. Augury, which Qualcomm recently invested $8 million in its Series C, offers a similar product and aims to catalyze a wave of valuable IoT manufacturing technologies that are possible with 5G.

智能制造工廠需要對出現故障的機械或過程故障做出快速響應。 當5G帶來更高的安全性和超低延遲時,工廠可以将非敏感資料發送到生活在雲中的平台和資源密集型AI進行分析,然後立即在工廠進行響應。 Petasense是一個很好的例子。 工廠将Petasense裝置放置在機器上,然後将加速度計資料發送到使用AI的雲平台。 借助雲的計算能力和工廠中IoT傳感器的資料的組合,AI可以檢測出故障的機器并将信号發送給工廠以關閉并安排維護。 高通最近在其C系列中投資了800萬美元,提供了類似的産品,旨在催生一波有價值的物聯網制造技術浪潮,這可能是5G可能的。

5G物聯網的局限性 (Limitations of 5G Powered IoT)

5g 為什麼需要邊緣雲_5g将雲的力量帶到了邊緣 背景 (Background) 遷移到雲端 (Moving to the Cloud) 5G物聯網的局限性 (Limitations of 5G Powered IoT) 物聯網公司在5G革命期間取得成功的政策 (Strategies for IoT Companies to Succeed During the 5G Revolution)

Photo by PAUL SMITH on Unsplash PAUL SMITH在 Unsplash上的 照片

The IoT landscape is about to go through a 5G-powered revolution, but not everything will change. Some IoT applications will still have to remain at the edge in this new world. What applications will remain at the edge? Throughout this piece, I referred to costs of communicating large amounts of data, unique security needs, and ultra-fast speed requirements as the reasons IoT hasn’t made its way to the cloud. Though 5G will greatly tackle these needs, it will still fall short for some applications.

物聯網領域将經曆一場由5G推動的革命,但并非一切都會改變。 在這個新世界中,某些物聯網應用仍将必須保持優勢。 哪些應用程式将保留在邊緣? 在整篇文章中,我都提到了通信大量資料的成本,獨特的安全需求和超高速需求,這是物聯網尚未進入雲的原因。 盡管5G将極大地滿足這些需求,但對于某些應用程式來說仍将不足。

Maximum Security Requirements

最高安全要求

Though 5G will offer incredible security via virtualization and network slicing, this security in communication doesn’t make the cloud servers your data is stored in any more or less secure, and so many applications will still opt to stay at the edge for higher security guarantees. 5G might still be utilized in these IoT devices, but as a means of getting data from distanced devices to a local server rather than to the cloud. Some applications that might fit into this bucket include industrial control systems and plant automation, such as Veo Robotics ‘ product which tracks human movement in order to allow safe collaborative work with automated machines. We might also see some hybrid approaches here to get the benefits of the cloud while keeping most of the security of hosting data at the edge, such as storing data on local servers, but then allowing a platform for operational management running in the cloud to access the local data.

盡管5G将通過虛拟化和網絡切片提供令人難以置信的安全性,但是這種通信安全性并不能使您的資料存儲在雲伺服器上或多或少地安全,是以許多應用程式仍會選擇留在邊緣以獲得更高的安全性保證。 。 5G可能仍會在這些IoT裝置中使用,但它是一種将資料從遠端裝置傳輸到本地伺服器而不是雲的方法。 可能适合該存儲桶的某些應用包括工業控制系統和工廠自動化,例如Veo Robotics的産品,該産品跟蹤人類的活動,以便與自動化機器進行安全的協作。 我們可能還會在這裡看到一些混合方法,以獲得雲的好處,同時将托管資料的大部分安全性保持在邊緣,例如将資料存儲在本地伺服器上,然後允許運作在雲中的營運管理平台通路本地資料。

Still Too Much Data

資料仍然太多

The cloud can offer more cost effective computation, but there’s still a cost to get your data to the cloud server. While 5G is expected to decrease this cost, there still exists a tradeoff, and so some use cases will still find it worthwhile to keep the data processing at the edge. A good example of this is automated security systems. If an application consumes gigabytes of video data in a day, but all it needs to do with it is check if anything has changed frame-to-frame, then the engineer might keep this simple computation close to the camera and only send up data when something has changed, like Reolink ‘s Argus 2 camera does.

雲計算可以提供更具成本效益的計算,但是将您的資料傳輸到雲伺服器仍然存在成本。 雖然預計5G可以降低成本,但仍然存在折衷,是以某些用例仍然認為值得在邊緣進行資料處理。 自動化安全系統就是一個很好的例子。 如果應用程式一天要消耗數十億位元組的視訊資料,但要做的隻是檢查幀間是否發生了任何變化,那麼工程師可能會将這種簡單的計算保持在錄影機附近,并且僅在以下情況下才發送資料:發生了一些變化,例如Reolink的Argus 2相機。

Optimally Minimal Latency

最佳最小延遲

While 5G has lightning fast latency characteristics (theoretically as fast as 1–4 ms), it will still add that time, plus the time to get a response from a server, to any process that relies on it to run an application in the cloud. In some settings, the value of every millisecond is greater than the benefits gained from using cloud computing. A great example of an application that will not leave the edge for this reason is the AI for autonomous vehicles, like that which May Mobility is creating. When you write a feature that will enable a vehicle to detect a pedestrian or a car, you will shave off every millisecond you can from the sensor making the measurement to the vehicle hitting the brakes. At the end of the day, you don’t want the reason a car hit someone to be that a cloud server, for whatever reason, took too long to respond.

盡管5G具有閃電般的快速延遲特性(理論上最快為1-4毫秒),但它仍然會增加該時間以及從伺服器獲得響應的時間,并依賴該時間來在雲中運作應用程式的任何程序。 在某些情況下,每毫秒的值大于使用雲計算所獲得的收益。 出于這一原因而不會落後的應用程式的一個很好的例子是自動駕駛汽車的AI,例如May Mobility正在建立的AI。 當您編寫使車輛能夠檢測到行人或汽車的功能時,您會從進行測量的傳感器到車輛踩下刹車的每一毫秒内剃光。 歸根結底,您不希望汽車撞到某人的原因是雲伺服器(無論出于何種原因)花費了太長時間做出響應。

物聯網公司在5G革命期間取得成功的政策 (Strategies for IoT Companies to Succeed During the 5G Revolution)

5g 為什麼需要邊緣雲_5g将雲的力量帶到了邊緣 背景 (Background) 遷移到雲端 (Moving to the Cloud) 5G物聯網的局限性 (Limitations of 5G Powered IoT) 物聯網公司在5G革命期間取得成功的政策 (Strategies for IoT Companies to Succeed During the 5G Revolution)

So change is coming, for better or worse, and for most it will be for the better! But if you are a company working in the IoT space and are concerned about 5G being a disruptive force, what can you do about it? I propose two strategies, and since this shakeup is around the future of product in IoT, the strategies are centered around product.

是以,無論好壞,變革都将到來,對于大多數人來說,它将變得更好! 但是,如果您是一家從事物聯網領域工作的公司,并且擔心5G是一種破壞性力量,那麼您将如何做? 我提出了兩種政策,并且由于這種變革是圍繞物聯網産品的未來發展的,是以這些政策以産品為中心。

First of all, as noted earlier, not all of IoT will be moving to the cloud. If your product is focused on applications that will stay at the edge, then you will be in a strong position for the next decade as your customers remain largely unaffected. One great example of this is one of our portfolio companies, Foghorn. Foghorn specializes in applying intelligent algorithms at the edge for industrial processes, and with the type of data they work with, many of their customers’ applications are going to be staying at the edge. First of all, the data can be sensitive, involving videos of manufacturing plant workers used to detect whether safety equipment is being appropriately worn and data on plant-specific operations that contain valuable IP for the company. Secondly, much of the data is massive, consisting of video streams, and would cost more to stream to a cloud server than it would to process locally with Foghorn’s edge-optimized AI. While many of their applications will likely remain at the edge, Foghorn is also well-positioned to take advantage of 5G for uses such as ultra-low latency automation.

首先,如前所述,并非所有的物聯網都将遷移到雲中。 如果您的産品專注于将保持優勢的應用程式,那麼在未來十年中您将處于優勢地位,因為您的客戶在很大程度上不會受到影響。 一個很好的例子就是我們的投資組合公司之一Foghorn 。 Foghorn專門在工業流程的邊緣應用智能算法,并且由于使用的資料類型不同,許多客戶的應用程式仍将停留在邊緣。 首先,資料可能很敏感,涉及用于檢測安全裝置是否被适當磨損的制造工廠勞工的視訊,以及包含該公司寶貴IP的工廠特定操作的資料。 其次,許多資料是巨大的,由視訊流組成,流向雲伺服器要比使用Foghorn的邊緣優化AI在本地處理要花費更多。 盡管他們的許多應用程式可能仍處于邊緣狀态,但Foghorn的定位也很不錯,可以利用5G進行超低延遲自動化等用途。

The second strategy is to focus on creating value in the IoT space independent of where the data is hosted or where the computation is happening. Anylog, a new startup, does exactly this. Their product allows you to navigate a decentralized IoT graph of data storage and computational resources, wherever the different hardware may be, as a singular centralized database. This product does not care if the data is stored in the cloud, at the edge, or a mix of the two. It also doesn’t care if the hardware for the computation you perform on the data is near the edge or in the cloud. It allows you to abstract all of that detail away, and parse the data as if it were collected in a single place. This kind of offering will keep companies valuable after 5G shifts many IoT applications to the cloud. This product strategy can even provide an advantage to companies that decide to shift from the edge to the cloud, as these companies would parse their data the same way before and after the shift.

第二種政策是專注于在IoT空間中創造價值,而與托管資料的位置或進行計算的位置無關。 新啟動的Anylog正是這樣做的。 他們的産品使您可以将資料存儲和計算資源的分散式IoT圖導航為單個集中式資料庫,而無論硬體在哪裡。 該産品不關心資料是存儲在雲中,在邊緣還是在兩者的混合中。 它也不在乎您對資料執行計算的硬體是在邊緣還是在雲端。 它使您可以抽象所有這些細節,并像将其收集在單個位置一樣分析資料。 在5G将許多IoT應用程式轉移到雲後,這種産品将使公司保持價值。 這種産品政策甚至可以為那些決定從邊緣遷移到雲的公司提供優勢,因為這些公司在遷移之前和之後都将以相同的方式解析其資料。

Hopefully throughout this piece you’ve noticed a common thread about what 5G and the movement from the edge to the cloud will do for IoT. It’s not just about existing applications moving their data and compute from the edge to the cloud, it’s also about entirely new possibilities. With the constraints that 5G will relax for IoT, there will soon be an IoT explosion with new applications and new devices popping up everywhere to collect data or communicate to the edge from an AI running in the cloud. Somewhat ironically, as this centralization of computing resources to the cloud decreases costs, offers an incredibly robust back-end, and makes scaling trivial for IoT, it will cause a decentralization revolution. In the coming decade, countless IoT products will flourish in a beautiful symbiosis between lightweight devices at the edge, cloud computing resources in the back-end, and 5G in the middle to communicate between the two.

希望在整個文章中,您已經注意到有關5G以及從邊緣到雲的移動将為IoT做些什麼的共同話題。 這不僅涉及現有應用程式将其資料和計算從邊緣遷移到雲,還涉及全新的可能性。 鑒于5G放寬物聯網的限制,不久将出現物聯網爆炸式增長,新應用程式和新裝置随處可見,以通過雲中運作的AI收集資料或與邊緣進行通信。 具有諷刺意味的是,由于将計算資源集中到雲中可以降低成本,提供令人難以置信的強大後端,并使物聯網的擴充變得微不足道,這将引發分散化革命。 在未來十年中,無數的物聯網産品将在邊緣的輕量級裝置,後端的雲計算資源以及中間的5G之間實作美好的共生,進而在兩者之間進行通信。

Originally published at https://medium.com on August 13, 2020.

最初于 2020年8月13日 釋出在 https://medium.com 。

翻譯自: https://medium.com/@DarlingVentures/5g-brings-the-power-of-cloud-to-the-edge-bdaad4b658a0

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