Countless presentations, articles and research papers propose use cases for edge computing today.

The authors of these propose everything from supporting billions of smart devices to reshaping the very plumbing of the internet itself, and many of these ideas and concepts hold significant promise for the future. However, use cases that can be put into practice today are extremely important, as they help advance the economic and technical elements driving the adoption of edge computing, ensuring the infrastructure needed to support other uses is created.

Luckily, there is no shortage of interestingand valuable use cases that are being readily explored today at the edge. As isdescribed below, these uses cases range from what could be referred to asinfrastructure transformation, where edge computing is used to augment orreimagine the underlying systems upon which many edge use cases may be built,to more specific activities such as supporting the use of autonomous drones andother low-latency devices that require new edge resources.

There are many different types of edgecomputing. However, this article focuses on what is known as infrastructure edge computing, asdefined in the Open Glossary of Edge Computing. This modelpositions elastic, cloud-like compute, storage and network resources as closeas possible to their users on the operator side of the last mile network, whetherthat network itself is wireless or wired, to provide scalable low-latencyoperation for a range of use cases.

The three use cases described below representsome of the most promising edge deployments of today. They are being activelydeployed at the edge by a range of companies, both large and small, establishedand emerging. What they all have in common is their reliance on robust edgecomputing infrastructure to make them a true reality:

For any vehicle, whether operating on land, inthe air or at sea, rapid decision-making ensures safe and reliable operation.Machines are capable of many things, but their ability to interpret potentialissues in the real world is far more limited than our own. In the case of fullyautonomous drones operating Beyond Visual Line of Sight (BVLOS), the targetlatency between the drone and its control applications is under 10 ms. Becausea drone has serious weight constraints, the most robust autonomous controlsnecessitate the use of infrastructure edge computing, where decision-supportapplications such as telemetry, collaborative processing and radar can bedelivered within this tight latency limit. The alternatives are unsafe,inefficient or manual operation.

In many cases, in todays legacy environments,the traffic that a device sends to the internet may take a long andcircuitous path, adding unnecessarytransport costs and latency. For example, data communication between two devices in the same city may, infact, traverse long distances, often spanning multiple states in the UnitedStates, before it reaches its destination. This is due to the way telecomsnetworks have been built, utilizingcomparatively few points of centralized aggregation that are able to exchangedata between networks. These Internet Exchange (IX) points are vital to theoperation of the internet, but in many emerginguse cases require a new and complementary entity, the Edge Exchange (EX).The EX augments the capabilities of the IX by allowing traffic which would staywithin a city to be exchanged much closer to its intended users, allowing theirlatency limitations to be met, while continuing to pass on Internet-boundtraffic to the traditional IX, as is already done today.

To allow greater flexibility, reduce costs andimprove performance, the Virtualized Radio Access Network (VRAN) and networksupgrades to 5G are hot topics for many wireless network operators, includingmany of the large, household name cellular carriers in the United States. Whenthe RAN is virtualized and many of the key radio functions can bedisaggregated, the result is a simpler and more flexible network However, these virtualized network functionsneed to perform complex processing in close proximity to the cell tower orradio head, under strict latency constraints. Infrastructure edge computingsites provide an ideal environment in which to run these functions, offeringthe dense compute, storage and network resources required to support these newcapabilities across many wireless network sites in the area.

Edge computing uses cases like those describedhere can add great value to almost any aspect of the wider technologylandscape. Many of these use cases are being deployed today at infrastructureedge computing sites, and those experiences are being presented to a wideraudience by leading companies in the edge computing ecosystem today.

Join Edgecon Austin, afternoon of 5thNovember, and Edge Congress 6th November, the premier event seriesto get up to speed on the latest happenings at the Edge.

http://www.edgecongress.com

Edgecon November 5th, 2019, 14:30 20:30 PMG

7CO 1501 E 7th St, Austin, TX 78702

Edge Congress November 6th 2019,09:00 20:30 PMG

Fair Market, 1100 E 5th St, Austin, TX 78702

Join the worlds top edge computing executivesat the Edge Global Congress. Industry players will be talking real deployments,solutions, and applications at the edge during this exclusive event.

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Finance is one of the core areas being migrated to the cloud. Key back-office functions such as Payroll, Accounting, Financial Planning, and Payments are among those that are already in the cloud, or are in the process of being moved off-premise.

That's according to a survey from Computing Research, which spoke to 150 senior enterprise IT decision makers, eight percent of whom are themselves in banking, finance, and insurance, and 27 percent of whom are in professional services, such as accountancy, property, and law.

With 13 percent of all respondents in industrial markets such as manufacturing, engineering, and pharmaceuticals, and the rest spread across major private sectors such as technology, telecoms, oil, gas, energy, mining, distribution, and transport, the survey can be seen as a significant vote in support of cloud migration, given those sectors' deep need for trust, reliability, and security.

Seventy-two percent of the survey base have up to 3,500 employees, 14 percent have between 3,500 and 10,000, and another 14 percent have more than 10,000 workers, so the research shows a major uptick in cloud adoption by medium-sized to larger organisations.

Finance in the cloud

Payments is the financial area that is most located in the cloud among these organisations, according to Computing Research: just over one-third of respondents (34 percent) currently host this function in the cloud, with a further 35 percent planning to move it in the near future. Just six percent of IT leaders still outsource Payments processing, while 22 percent plan to keep it on premises - revealing a clear shift away from traditional or legacy models.

Accounting is the next most popular finance-related function to move to the cloud, with one-third of respondents saying that it is already hosted off premises and another third planning the move in the near future. Just four percent of all respondents outsource Accounting, which leaves 29 percent planning to keep the function on premises.

Payroll is just behind, with 32 percent of organisations having already migrated to the cloud. However, significantly fewer respondents - 26 percent - are planning the move in future. With just 17 percent keeping the function on premises, this leaves 22 percent outsourcing it, making it the most popular area to entrust to a third-party specialist.

The more strategic function of Financial Planning sees a smaller shift to the cloud: just under 30 percent of respondents have already migrated it, with the same number planning the move in future. Unsurprisingly, the proportion of organisations outsourcing it is small - less than five percent - which leaves 30 percent planning to keep the function on premise. A significant proportion of IT leaders clearly see this as a comfort zone' for the business.

The broader back office

A broad range of related back-office functions are also being shifted to the cloud, found the survey, such as: Supply Chain Management (32 percent hosted in the cloud and 33 percent planning the move); Business Intelligence (38 percent hosted, 35 percent planning); Human Capital Management (HCM, 36 percent and 38 percent); Supply Chain Management (32 percent and 33 percent); Enterprise Resource Planning (ERP, 35 percent and 34 percent); and Professional Services Automation (28 percent and 30 percent).

All of these statistics show a clear majority of medium to large enterprises placing their confidence in cloud services and platforms, over and above the perceived safety (for some) of retaining on-premise solutions.

In the case of traditional or legacy on-premise solutions, only Financial Planning, Accounting, Supply Chain Management, and Payments have more than 20 percent support among the survey base, with only Financial Planning coming close to matching the proportions who are moving to the cloud.

Leaders & laggards

Overall, the results show a familiar split when it comes to cloud migration surveys: a third of pack leaders in the vanguard of digital transformation, a third of pack followers, and a third who are resistant to non-traditional ideas. However, the research shows that the leaders are growing as a pack, and the stragglers are diminishing.

Top of the list of reasons cited by the naysayers is security, mentioned by 42 percent of the group, followed by migration complexity (41 percent of naysayers). Compliance issues also rate highly on the list of negatives, cited by 40 percent of the pack. Also mentioned were low strategic priority (33 percent); risk aversion (30 percent); high costs (24 percent); lack of internal skills (17 percent); and the simple Don't see the need' (14 percent).

In a free answer, another response was "Have invested in on-premises, and need the investment to fulfil."

Among those that have moved functions to the cloud, 43 percent acknowledged that migration complexity had been a factor, and 40 percent that legacy hardware and software had been a challenge. Security was cited by fewer respondents as a real-world problem: 38 percent of respondents.

A notable finding was that lack of internal skills - cited by 40 percent of IT leaders - had been a much bigger negative for cloud adopters than for on-premise supporters who were worried about moving to the cloud.

This article is from Computing'sCloud ERP Spotlight, hosted in association withWorkday.

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Cloud now the destination for finance, says survey - http://www.computing.co.uk

What is the Solutions Review Cloud Insight Jam? What cloud computing, cloud management,and other information can you explain to learn from it? How can you participate?

We seek to answer these questions as we build up to the first ever Cloud Insight Jam on December 19th!

On December 19th, we begin an unprecedented social media day covering cloud computing in detail! During the Cloud Insight Jam, we plan to share our own best practices and the best practices from cloud experts; these experts come from cloud solution vendors from across the world. Additionally, we plan to share customer success stories from these providers and their predictions for 2020.

You can see all of it unfold on Twitter and LinkedIn under the hashtag #CloudInsightJam. Also, you can follow along on the Enterprise Cloud Strategy page of the Solutions Review website.

Absolutely! We plan on taking the day by storm!(All times listed below are in Eastern Standard Time.)

From 8:30 AM to 12:30 PM, the conversation will revolve around cloud best practices, including how enterprises can evaluate and select a cloud solution. At 10 AM, well host a half-hour open tech chat The Morning Dose. Well discuss cloud best practices personally, and exchange our thoughts with everyone!

From 12:30 PM to 4:30 PM, well shift the conversation to customer success stories. At 2 PM, we host a second half-hour open tech chat called the Re-Up! In this conversation, well cover how customers can achieve success with their cloud solutions.

From 4:30 PM to 8:30 PM, well end the day by focusing on industry trends and predictions for cloud in 2020. We want to discuss where the cloud is heading in the future, and what cloud solution users should look for in the new year.

Heres a sample of the questions we plan on sharing during the Morning Dose open tech chat:

This shouldnt be considered a definitive list of questions; were still cooking up some excellent conversation starters for the chat!

Unlike the Morning Dose, the Re-Up conversation at 2 PM EST will focus on customer success and predictions. Questions asked during the chat may include:

Just like the above, well have more questions on offer during the chat itself!

To participate in the Cloud Insight Jam, simply use the hashtag #CloudInsightJam on Twitter and LinkedIn. Keep an eye on the feed, participate in the chat, and share your thoughts!

Yes, itis that simple!

Sure! There is no cost to participate in the Jam, and you can participate as much as you would like! Want to join one of the conversations but not the other? Thats okay! Feel free to comment, question, or otherwise chat about any of the content we release throughout the day!

Weve extended the deadline for video content and best practices until December 6th. If you have video content you would like to share, please make sure it follows our video guidelines, which we share here. You can submit your content, video or otherwise, athttp://www.insightjam.com/.

Hope to see you at the Cloud Insight Jam on December 19th!

Looking for more info on managed service providers for your cloud solutions? Our MSP Buyers Guide contains profiles on the top cloud managed service providers for AWS, Azure, and Google Cloud, as well as questions you should ask vendors and yourself before buying. We also offer an MSP Vendor Map that outlines those vendors in a Venn diagram to make it easy for you to select potential providers.

Check us out onTwitter for the latest in Enterprise Cloud news and developments!

Dan is a tech writer who writes about Enterprise Cloud Strategy and Network Monitoring for Solutions Review. He graduated from Fitchburg State University with a Bachelor's in Professional Writing. You can reach him at dhein@solutionsreview.com

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What's Happening at the Cloud Insight Jam on December 19th? - Solutions Review

Cloud computing, in general terms, is the computing model that allows clients to use only a specific set of services that are required and pay only for them, in contrast to software tools or services that come bundled with a number of tools or services that are not needed. Cloud computing has become one of the most preferred computing models for the healthcare industry in its way to transformation from the conventional paper-based data storage and processing to the more sophisticated and advanced digitally aligned data model.

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https://www.transparencymarketresearch.com/cloud-computing-healthcare-development.html

By eliminating the need for a local server or a dedicated hardware system for the storage and access of data-heavy entities such as electronic health records (EHRs) and a variety of medical scan images, the cloud computing model provides the healthcare industry an infrastructure that allows for improved use of resources at low initial capital investment. Additionally, cloud computing models help in lowering the barriers for innovation and modernization of healthcare information technology systems and applications owing to their flexible nature, typically not possible with traditional IT solutions. In the area of research and development in the healthcare industry, cloud computing has demonstrated its capability of delivering improved services in a cost competitive manner.

This report on the global cloud computing in healthcare research and development market presents a detailed overview of the state of exploitation of the cloud model in these areas in the healthcare industry. The factors expected to impact the growth and overall development of the market, in positive or negative ways, are examined in great details. As such, the report presents an overview of factors such as drivers, restraints, trends, opportunities, and regulatory factors observed across key regional markets and on a global level..

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Cloud Computing Market in Healthcare Research and Development: Trends and Opportunities

The market is chiefly drive due to the rising expenditure of global pharmaceutical giants on research and development activities aimed at the development of next generation drugs and treatment methods. The globalization of key vendors in the pharmaceutical and biopharmaceutical industries, necessitating the establishment of R&D facilities, is also expected to remain central to the increased scope of adoption of cloud computing in research and development activities in the healthcare industry.

From a geographical perspective, the North America market for cloud computing in healthcare research and development dominates, accounting for the dominant share in the revenue of the overall market. The presence of a large number of some of worlds leading pharmaceutical and biopharmaceutical companies in the region is one of the key factors driving the high adoption of cloud computing for research and development activities in the healthcare sector. The Europe market, which follows North America in terms of market position and contribution of revenue to the global market, also fares well owing to the same factor the presence of a large number of leading pharmaceutical and biopharmaceutical companies.

Global Cloud Computing Market in Healthcare Research and Development: Competitive Analysis

The global market for cloud computing in healthcare research and development features an exceedingly fragmented vendor landscape. It has been observed that none of the players in the market hold more than 5%-10% share in the global market. With the rising adoption of cloud computing in research and development activities in the healthcare industries and the subsequent rise in growth opportunities offered by the market, a number of new players are expected to enter the market, making the competitiveness more intense.

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Some of the key companies in the market presently are Cisco Systems, Inc., Oracle Corporation, Intel Corporation, Microsoft Corporation, IBM Corporation, Carecloud Corporation, Carestream Health, Inc., and Merge Healthcare, Inc.

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Cloud Computing Market in Healthcare Research and Development Key Players, Industry Overview and Forecast Analysis - Montana Ledger

Since 1993, the IndustryWeek's Technology Leader of the Year feature has served as our platform to celebrate individuals who have successfully leveraged technology to reshape the manufacturing world. Manufacturing greats including Bill Gates, Elon Musk, Harley-Davidson's Jeff Bleustein and GM's Ralph Syzgenda have each taken home the honors.

As the year of the great digital transformation, 2019 saw some of the biggest advancements yet. After all these years of talk about the Internet of Things (IoT) and digital transformation defining the future health and progress for the manufacturing industry, the hype has finally delivered on its promise. Along the way, one company has established itself as the clear leader: Amazon. And, if the future of manufacturing depends on technology and IoT, then Amazon CTO Werner Vogels is the person that will make it possible.

Often referred to as one of the fathers of cloud computing, few others have had as much impact on the future of manufacturing as Vogels. This is especially true as Industry 4.0 has put an emphasis on the importance of digital technologies.

While the journey to revamp manufacturing may have started with cloud computing, it is the blend of data-driven technologies that positions Amazon and Vogels as the leader in this space. Specifically, it is technologies such data analytics, artificial intelligence, machine learning, IoT and edge computing that are ultimately enabling manufacturers to find success within the growing experience economy.

As Amazons CTO, Vogels is responsible for driving the company's customer-centric technology vision. Vogels joined Amazon in 2004 as the director of systems research after spending time as a distributed systems researcher at Cornell University. He assumed the roles of CTO and vice president the next year, and quickly surfaced as a key force behind Amazons approach to cloud computing.

When Amazon Web Services (AWS) first started offering its suite of transformative technologies (2004-2005) outside the company, Vogels team was primarily focused on collaborating with companies that needed to quickly achieve internet scale. In those days, they were mostly younger businesses or truly progressive enterprises that already had a clear digital future.

As such, Vogels acknowledges that manufacturing companies were not necessarily an immediate target and for good reason. At that time, manufacturers were overwhelmingly relying on decades-old equipment that was often singularly dedicated and lacking the ability to generate useable data. However, it did not take long for a digital evolution to transpire within the manufacturing sector.

It happened that many manufacturers were looking to completely revamp their infrastructure, says Vogels. They were interested in using cloud technology to make use of analytics as a key part of being smart manufacturers. That understandably meant finding ways to turn these singular devices into data generators, seamlessly moving the data to cloud, exploring machine learning and then capitalizing on the ability to push insights back into the plant environment.

Vogels has since worked closely with numerous manufacturers, taking the time to understand their current positions as well as their goals in embracing technology in order to capitalize on the digital realm. We have always had strong relationships with our customers and together we have developed solutions, he says. We do not go off into a high tower, build something and then give it to manufacturing customers. We learn about what they want their technology to look in five to 10 years, and make sure that we build tools that are ready for the manufacturer of the future. This introduced a whole new realm of functionality especially around device management, security and edge computing.

The cloud evolution has really moved beyond the phase of companies moving everything to the cloud with people abandoning all local processing. For quite a few internet and consumer driven companies that is the case. That is their reality, says Vogels. Yet, for manufacturing, the edge computing component is becoming extremely important. Manufacturers need to be able to operate in a disconnected mode, but still need to benefit from advanced processing capabilities, he says. This creates a very interesting challenge to collaboratively build technologies for devices that will spend a spectrum of time not just in the cloud, but on premise as well.

Vogels points to Amazons IoT Greengrass offering as a direct result of collaboration with manufacturers. Greengrass seamlessly extends AWS to edge devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. Whether or not there is an internet connection, devices can runAWS Lambdafunctions, execute predictions based on machine learning models, keep device data in sync, and communicate with other devices securely.

Manufacturers can get rich insights at a lower cost by programming devices to filter data locally and only transmit the data needed for applications to the cloud. Understandably, the goal is to reduce the amount of raw data the manufacturer sendsto the cloud, which ultimately minimizes the cost and increases the quality of the data transmitted. AWS is going a step further by integrating machine learning into edge devices. ML uses algorithms that learn from existing data, a process called training, to make decisions about new data, a process called inference. Because inference requires significantly less computing power than training and optimizing ML models, it occurs in real time when new data is available.

According to Vogels, getting inference results with low latency is important for making sure that IoT applications respond quickly to local events. Such local inference could allow a robot to make autonomous decisions in near-real time, even without a connection to the cloud.

Although AI is very a broad concept, the machine learning component and the ability to make use of the very large data sets continues to show potential, especially when considering the phenomenal amounts of data US manufacturers create daily. That is only going to grow tremendously, both in volume and importance, says Vogels.

Woodside Energy serves as a prime example. Initially, Woodsides Pluto Liquefied Natural Gas facility in Western Australia leveraged 10,000 sensors, primarily capable of alerting key personnel when faults occurred. However, being able to leverage cloud-based machine learning capabilities has proved transformative.

Today, Woodside uses sensor data to build an algorithm that allows the team to predict and prevent foaming in the Acid Gas Removal Unit (AGRU), a critical part of the production process that cannot be monitored directly. Currently, Woodside runs more than 6,000 algorithms on the sensor data from its Pluto plant. These same operations now make use of 200,000 sensors, monitor operations 24/7. By connecting these IoT sensors to the AWS Cloud, Woodside has been able to optimize the production and maintenance. This is a major shift from reacting to an alarm going off to being able to take data, analyze and immediately predicting potential issues, says Vogels.

Access to new datapoints is enabling Woodsides data science team to continuously find new insights by sharing data across the organization. Of course, the Woodside transformation is ongoing including a dedication to explore uses for AI to augment and inform better decision-making.

According to Vogels, many of the truly smart manufacturers have already passed through the barrier of Industry 4.0. And, some of these manufacturers have significant plans to fully capitalize on the digital realm. For example, in March 2019, AWS announced an ongoing cooperation agreement with Volkswagen (VW). As part of agreement AWS is building an industrial cloud for VW, which will connect all of VWs 122 global factories, enabling the automaker to seamlessly collect all of its data in real-time and put it into the cloud.

As VWs industrial cloud solidifies, the plan is to use the AWS IoT, machine learning, analytics and computing solutions for plant assembly efficiency, vehicle quality and production flexibility. These include more efficient control of material flow, the early detection and elimination of supply bottlenecks and process disruptions, and the optimized operation of machinery and equipment in all plants. In addition, the cloud-based platform with its simplified data exchange is an essential prerequisite for Volkswagen to provide new technologies and innovations rapidly across its various locations. These include smart robotics, and data analysis functions to analyze and check shop floor processes from plant to plant. With the cloud-based platform, new applications, for example in IT-security for shop floor systems, can be scaled up direct to all locations throughout the world. Volkswagen will leverage AWS innovation best practices to become more agile and react faster on industry trends.

The architecture will be the new Digital Production Platform (DPP) from Volkswagen in future. All the Groups plants and companies outside the Group will dock their system architectures onto this platform. This platform will standardize and simplify data exchange between systems and plants. This is key step to enabling the type of comprehensive analytics that fuel maintenance and anything else a progressive manufacturer can get out of data, says Vogels.

For Vogels, continuing to expand machine learning, IoT and edge computing will remain key focus areas for his team. However, security is the top priority. And it is also an area where his team has worked to be innovative. As we work to bring legacy devices online in one form or another whether it is into a private network, into the cloud or into a private network linked to the cloud we need to recognize that this data is crucial to the manufacturing organization. It is industrial gold. We need to make sure that our customers are protected there. Now more than ever security needs to be the top priority, he says.

A big piece of the puzzle? Building new tools that enable manufacturers to take actions to help themselves, explains Vogels. Machine learning will play an increasingly important role here. You cannot build one service that works for all of your customers, especially when it comes to security. You need to be able to learn from the environment.

Technology is almost always being used for a particular task no one is creating technology for technology sake. Yet talent is lacking for most companies and continues to be the biggest challenge. At the same time, most companies have decided that cloud is the future whether they are using it for analytics, product development or to dynamically control the entire supply chain. It is interesting to watch companies who have traditionally been slow moving, because of the massive investments they have into their assets, are now are moving full force into the digital domain, explains Vogels.

They are managing a completely new world for them, and in many cases, without any access to digital talent. As cloud technology slightly settles down, the focus is now on how can we train people fast enough, so that all of these companies that are either going through or need to go through the digital transformation actually have access to the talent that they need, he says. We are looking forward to helping establish educational programs.

Vogels is passionate about helping manufacturers successfully go through the digital transformation. After all, thats where the real future of manufacturing thrives.

Giving manufacturers the right tools, so that they can focus on what they actually want to do with their data as they continue to optimize operations, he says. This is true whether its Siemens Healthcare building machinery that has IIoT fully integrated or a smart manufacturer who still needs to be able to move back and forth between the cloud and on-prem. We need to make sure that we are building technologies that they can use five to 10 years from now because that is the process manufacturers go through.

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Technology Leader of the Year: Enabling the Digital Transformation - IndustryWeek