Networks can call on a growing armoury of connection technologies, but there’s another revolution happening too – a much greater role is emerging for data processing at the network edge than was envisaged for the Industrial Internet of Things (IIoT). Jeremy Cowan reports.
The Internet of Things (IoT) was enabled by cloud-based intelligence with IoT devices at the network edge sending data back to the cloud for storage and analysis. However, that data can’t be analysed and actioned in real-time. Also, it can be costly to transmit vast quantities of data, plus data security and privacy can be put at risk during transfer. Cloud-native solutions give device operators insights into their applications’ performance, but for real-time services this is historical.
Some IoT users now expect service providers to anticipate problems using predictive analytics which need real-time data. Artificial intelligence (AI) and machine learning can optimise the performance of farms, factories, vehicle fleets, or oil & gas installations, and the best way to achieve that is through edge computing.
Edge computing can:
- Minimise the cost of data transfer to the cloud
- Speed data analysis
- Generate actionable intelligence at the device, where it’s needed
- Reduce data privacy and security risks by removing personal identifiers before data transfer
- Enable decisions to be made locally with support from AI and streaming analytics, and
- Provide always-on computing where internet connections fail or are intermittent.
Strategy first
MobiledgeX is helping IoT end users to evaluate their aims and needs. It is a wholly-owned subsidiary of Deutsche Telekom (DT), with headquarters in San Francisco, which aims to help jump-start industry-wide collaboration. MobiledgeX recently published a findings from a three-year research initiative based on one-to-one interviews with more than 200 businesses around the globe about their planned edge strategies. The data is available to interested parties and the company is inviting industries to contribute to it.
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of IoT Global Network
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The research found multi-player and cloud gaming, V2X communications, and Industrial IoT are among the most viable near-term edge use cases, based on nine critical market and edge-related factors. The results of the research effort are summarised in independent data analysis from industry analyst, Chetan Sharma in the “Edge Computing Framework: Understanding the Opportunity Roadmap” report.
MobiledgeX’s Early Access programme provides developers with free access to live edge infrastructure, consultative support, discovery and guidance from a team of edge experts. It also offers promotional support and opportunities to network with other edge application developers. The company has begun accepting applications for the sixmonth programme and aims to target developers in Europe, North America, and Asia across the rest of this year.
Sunay Tripathi, CTO and EVP of Engineering for MobiledgeX, said, “We’re excited for our Early Access programme members to begin optimising their applications to leverage the edge and trial it in actual live edge networks to fasttrack their journeys to the delivery of next-generation user experiences.”
Developers whose applications are accepted will join the likes of organisations such as 1000 realities which is already working with MobiledgeX. “Edge computing delivers the low latency that allows us to offer users of our augmented reality spatial mapping and positional platform the highest precision for a flawless experience, which will help us quickly and seamlessly scale our business across the globe,” said Justyna Janicka, co-founder and COO of 1000 realities.
Low latency and costs
Reduced latency and cost optimisation are key factors driving the adoption of edge technology. There’s also a big role for programmable embedded software that can provide enhanced security and enables task execution at the edge, which is why Minnesota-based MultiTech Systems, Inc. recently introduced its mPower Edge Intelligence.
MultiTech is a global supplier of machine-to-machine (M2M) and IoT communication solutions. Its mPower Edge Intelligence is an embedded software offering, building on its application enablement platform to deliver programmability, network flexibility, enhanced security and manageability for scalable IIoT solutions.
“When it comes to adding value and making smart choices, particularly related to security, the ability to make decisions at the edge of Industrial IoT networks is an absolute must,” said Prasad Kandikonda, vice president of Engineering, MultiTech. “mPower Edge Intelligence reflects what we’ve learned from more than five years delivering smart devices to a variety of industries and applications that require device programmability, security and dependable upgrade paths across our product lines.”
mPower unifies the MultiTech smart router and gateway firmware platforms. It means that MultiConnect rCell 100 Series customers can gain the programmability of the MultiConnect Conduit gateway, while gateway customers can benefit from the extra security features available on the rCell.
Analytics at the gateway or edge
mPower Edge Intelligence is designed to simplify integration with popular upstream IoT platforms and streamline edge-to-cloud data management and analytics. It also has the programming and processing capability to execute critical tasks at the edge to: reduce latency; control network and cloud services costs; and ensure core functionality. It even enables this when network connectivity is not available.
Another common driver in IIoT is deploying analytics closer to the endpoint. As points out, with an IoT edge gateway you can use AI services locally to process data from downstream devices without sending full telemetry to the cloud. It may only be necessary to send a subset of your data to the IoT hub.
A gateway can isolate a downstream device, protecting it from exposure to the internet and sit between an Operations Technology (OT) network with no connectivity and an Information Technology (IT) network that can access the web.
There are other benefits of using IoT edge devices as gateways: all devices connected to the IoT hub through the gateway use the same connection; it can smooth traffic flows while persisting with local messaging; and the gateway device can store messages and twin updates that cannot be delivered to IoT hub (for example, due to occasional or failed connectivity).
As Microsoft adds, an IoT edge device can also be used as a gateway to other devices: “Devices that cannot connect to the IoT hub can connect to a gateway device instead. The gateway provides IoT hub identity and protocol translation on behalf of the downstream devices. The gateway is smart enough to understand the protocol used by the downstream devices, provide their identity, and translate IoT Hub primitives.”
Partial connection or disconnected environments are also addressed by Flexera’s FlexNet Edge, a component of its Software and IoT Monetisation Platform. The smart edge server enables updates and gathers device data from partially connected or disconnected environments. It also provides full automation and control for the delivery and deployment of software and firmware updates.
Deliberately disconnected
There are key use cases where applications and devices remain intentionally disconnected from the Internet – including high security business applications, highperformance computing software, industrial equipment and medical devices.
Suppliers need to keep these applications and devices up-todate and secure. Buyers benefit from staying current, gaining access to the latest features, reducing support costs and downtime. In addition, says Flexera, insights gained from device status data allows suppliers to maintain an audit trail of software versions that have been deployed to specific devices. This data is valuable for making informed support and maintenance decisions, and in some cases is a regulatory requirement as in the USA’s FDA Medical Device Safety Action Plan.
Matthew Dunkley, Flexera’s senior director of strategy and product management, says, “FlexNet Edge extends our stateof-the-art solutions to the edge and into high security environments, including medical and industrial facilities. Our Software and IoT Monetisation platform provides a centralised management solution for all applications and devices – whether they’re connected or disconnected.”
Retail and transport
Applications of edge computing in the IoT are varied. New York-based Veea Inc., for example, was founded in 2014 and offers edge solutions for enterprise and mobile network operators to deploy applications at the network edge. Its Platform-as-a-Service (PaaS) supports verticals as diverse as retail, smart cities and connected healthcare. Stand-alone wired, wireless and computing solutions have limitations not shared by VeeaHub’s hybrid connectivity that underpins what Veea says is a low-cost, ultra-reliable platform based on edge computing and its vMesh solution.
In shops the RetailHub can connect security cameras to the control centre to record and review footage. Security systems can be integrated with other stores and security services. Customer experience can be enhanced too, as in-store marketing and digital signage lets customers know about frequent changes to special offers, discounts and new products. As customers enter a retail zone, perhaps selling phones and tablets, proximity marketing enables the retailer to target customers interested in these product lines. And in a clothes store, inventory and purchases can be readily tracked and analysed.
co-founder and COO
1000 realities
senior director of strategy
and product management
Flexera
vice president, product
Line management
Sierra Wireless
director of strategy
Netcracker Technology
Meanwhile, travellers increasingly expect transport services, such as trains and buses, to offer connectivity on the move that is comparable to their home or office. In reality, service speed and reliability is inevitably compromised in a fastmoving vehicle covering long distances. Veea’s CEO, Allen Salmasi reports, “This can be addressed by installing an edge node inside the train itself, which manages connectivity and data processing locally, to avoid the need to communicate with distant servers.”
An edge node can improve the speed and quality of response for online applications, but there are still challenges in fitting them across an entire railway fleet, since most carriages have a 40-year replacement cycle. Veea claims that its SmartTransport Hub offers an “affordable solution” which can be retrofitted to older rolling stock to deliver reliable connectivity and data services on the move.
Asked where he believes the biggest breakthroughs will be in market deployments, Salmasi said, “I guess in small, independent shops. They want 4G failover, because the internet can go down a lot in remote areas, so this (RetailHub) sustains payment facilities. We can also offer payment services replacing expensive Points of Sale (PoS). Traditional PoS is US$400-700 each, this is $50-70 and could even be free if there is a large volume opportunity.”
Energetic solutions
A provider of integrated device-to-cloud solutions for the IoT, Sierra Wireless has joined Duke Energy and Open Energy Solutions (OES) to develop an intelligent edge platform to run more complex, centrally managed and containerised edge applications.
The robust edge platform uses Sierra Wireless AirLink cellular gateways and Duke Energy’s Emerging Technology Office’s work on the Open Field Message Bus standard. They aim to provide more decision-making capabilities at the edge, interoperability between the various smart grid elements and faster decision making.
Dr. Stuart Laval, director of technology at Duke Energy says, “This collaboration will leverage a ratified, robust networking platform with faster edge processing capabilities to enable next-generation applications, including advanced distribution automation and distributed energy resources integration that are key to delivering on the future of smart grids.” The Sierra Wireless platform is based on open standards, enabling more application and grid solution providers to deploy a variety of innovative solutions using AirLink gateways that help utilities manage smart grids of the future by: enhancing situational awareness for faster response times and service restoration; integrating distributed energy resource and microgrids more efficiently; and improving security and interoperability for existing grid equipment and infrastructure. Tom Mueller, vice president, Product Line Management, Sierra Wireless adds, “The distributed grids of the future will rely on intelligent edge processing to provide uninterrupted service, while bridging old and new technologies.”
Don’t all rush to the edge
Finally, edge computing is not a panacea for all problems and Paul Hughes, director of strategy at Netcracker Technology, offers some words of caution. Although progress has been made with standards, such as multi-access edge computing (MEC), Hughes explained, “The level of capability in today’s devices grows almost exponentially every year thanks to faster processors, greater levels of storage, and faster connectivity to the internet. This strength of functionality at the edge shifts computing needs from a centralised data centre, to allow newer decentralised IoT applications.
“This does create greater challenges for keeping IoT services ‘intelligently operating’, as greater power to the individual end point requires greater management of the entire IoT device ecosystem. As intelligence grows, the promises of edge-based computing bring the need for intelligent device management, which comprises realtime data analytics, security and identity control functions, and even service assurance in cases of mission critical service offerings.
“Any operator looking to offer or manage IoT services on behalf of a customer, industry or business group must invest in solutions that ensure service continuity and service security, and use those tools to optimise the service to a service level agreement-centric level. This isn’t an easy turn-key solution process. Service providers must plan well ahead, and design a comprehensive IoT edge management blueprint and long-term strategy that provides a full risk assessment, evaluates expected service activity expectations, business outcomes and long term vision before jumping in head first.”