5G Will Accelerate a New Wave of IoT Applications and Z

Even before the advent of 5G DancingDinosaur, which had ghostwritten a top book on IoT, believed that IoT and smartphones would lead back to the Z eventually, somehow. Maybe the arrival of 5G and smart edge computing might slow the path to the Z. Or maybe not.

Even transactions and data originating and being processed at the edge will need to be secured, backed up, stored, distributed to the cloud, to other servers and systems, to multiple clouds, on premises, and further  processed and reprocessed in numerous ways. Along the way, they will find their ways back to a Z somehow and somewhere, sooner or later.

an edge architecture

“5G is driving change in the Internet of Things (IoT). It’s a powerful enabling technology for a new generation of use cases that will leverage edge computing to make IoT more effective and efficient,” writes Rishi Vaish and Sky Matthews. Rishi Vaish is CTO and VP, IBM AI Applications; Sky Matthews is CTO, Engineering Lifecycle Management at IBM.  DancingDinosaur completely agrees, adding only that it won’t just stop there.

Vaish and Matthews continue: “In many ways, the narrative of 5G is the interaction between two inexorable forces: the rise in highly reliable, high-bandwidth communications, and the rapid spread of available computing power throughout the network. The computing power doesn’t just end at the network, though. End-point devices that connect to the network are also getting smarter and more powerful.” 

True enough, the power does not just end there; neither does it start there. There is a long line of powerful systems, the z15 and generations of Z before it that handle and enhance everything that happens in whatever ways are desired at that moment or, as is often the case, later. 

And yes, there will be numerous ways to create comparable services using similarly smart and flexible edge devices. But experience has shown that it takes time to work out the inevitable kinks that invariably will surface, often at the least expected and most inopportune moment. Think of it as just the latest manifestation of Murphy’s Law moved to the edge and 5G.

The increasingly dynamic and powerful computational environment that’s taking shape as telcos begin to redesign their networks for 5G will accelerate the uptake of IoT applications and services throughout industry,  Vaish and Matthews continue. We expect that 5G will enable new use cases in remote monitoring and visual inspection, autonomous operations in large-scale remote environments such as mines, connected vehicles, and more.

This rapidly expanding range of computing options, they add,  requires a much more flexible approach to building and deploying applications and AI models that can take advantage of the most cost-efficient compute resources available.

IBM chimes in: There are many ways that this combination of 5G and edge computing can enable new applications and new innovations in various industries. IBM and Verizon, for example, are developing potential 5G and edge solutions like remote-controlled robotics, near real-time video analysis, and other kinds of factory-floor automation.

The advantage comes from smart 5G edge devices doing the analytics immediately, at the spot where decisions may be best made. Are you sure that decisions made at the edge immediately are always the best? DancingDinosaur would like to see a little more data on that.

In that case, don’t be surprised to discover that there will be other decisions that benefit from being made later, with the addition of other data and analysis. There is too much added value and insight packed into the Z data center to not take advantage of it.

Alan Radding, a veteran information technology analyst, writer, and ghost-writer, is DancingDinosaur. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/.

Apps and Ecosystem Critical for 5G Edge Success

According to the gospel of IBM, Edge computing with 5G creates opportunities in every industry. It brings computation and data storage closer to where data is generated, enabling better data control, reduced costs, faster insights and actions, and continuous operations.

Edge computing IBM Cloud Architecture

By 2025, 75% of enterprise data will be processed more efficiently on devices at the edge, compared to only 10% today. It will eliminate the need to relay data acquired, and often used for decision making in the field back to a data center for processing and storage. 

In short, the combination of 5G and smart devices on the edge aids this growing flow of data and processing through the proliferation of a variety of clouds: private, public, multi, and hybrid. But more is needed.

To get things rolling, IBM announced a handful of applications and tools and an edge ecosystem. As IBM notes: organizations across industries can now fully realize the benefits of edge computing, including running AI and analytics at the edge to achieve insights closer to where the work is done and the results applied. These new solutions include:

• IBM Edge Application Manager – an autonomous management tool to enable AI, analytics and IoT enterprise workloads to be deployed and remotely managed, delivering real-time analysis and insight at scale. It aims to enable the management of up to 10,000 edge nodes simultaneously by a single administrator. It is the first to be powered by Open Horizon, which is folded into the Linux Foundation. 
• IBM Telco Network Cloud Manager – runs on Red Hat OpenShift and Red Hat Open Stack,  a cloud computing platform that virtualizes resources from industry-standard hardware, organizes them into clouds, and manages them to provide new services now and going forward as 5G adoption expands.
• A portfolio of edge-enabled applications and services, including IBM Visual Insights, IBM Production Optimization, IBM Connected Manufacturing, IBM Asset Optimization, IBM Maximo Worker Insights and IBM Visual Inspector. All aim to deliver the flexibility to deploy AI and cognitive applications and services at the edge and at scale. 
• Red Hat OpenShift, which manages containers with automated installation, upgrades, and lifecycle management throughout the container stack—the operating system, Kubernetes cluster services, and applications—on any cloud.
• Dedicated IBM Services teams for edge computing and telco network clouds that draw on IBM’s expertise to deliver 5G and edge-enabled capabilities across all industries.

In addition, IBM is announcing the IBM Edge Ecosystem, through which an increasingly broad set of ISVs, GSIs and more will be helping enterprises capture the opportunities of edge computing with a variety of solutions built upon IBM’s technology. IBM is also creating the IBM Telco Network Cloud Ecosystem, bringing together a set of partners across the telecommunications industry that offer a breadth of network functionality that helps providers deploy their network cloud platforms. 

These open ecosystems of equipment manufacturers, networking and IT providers, and software providers include Cisco, Dell Technologies, Juniper Networks, Intel, NVIDIA, Samsung, Packet, Equinix Company, Hazelcast, Sysdig, Turbonomic, Portworx, Humio, Indra Minsait, Eurotech, Arrow Electronics, ADLINK, Acromove, Geniatech, SmartCone, CloudHedge, Altiostar, Metaswitch, F5 Networks, and ADVA as members. 

Making the promise of edge computing a reality requires an open ecosystem with diverse participants. It also requires open standards-based, cloud native solutions that can be deployed and autonomously managed at massive scale throughout the edge and can move data and applications seamlessly between private data centers, hybrid multiclouds, and the edge. IBM has already enlisted dozens of organizations in what it describes as its open edge ecosystem.  You can try to join the IBM ecosystem or start organizing your own.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/

5G Joins Edge Technology and Hybrid Multicloud

At IBM’s virtual Think Conference the first week in May the company made a big play for edge computing and 5G together. 

From connected vehicles to intelligent manufacturing equipment, the amount of data from devices has resulted in unprecedented volumes of data at the edge. IBM is convinced the data volumes will compound as 5G networks increase the number of connected mobile devices.

z15 T02  and the LinuxONE 111 LT2

Edge computing  and 5G networks promise to reduce latency while improving speed, reliability, and processing. This will deliver faster and more comprehensive data analysis, deeper insights, faster response times, and improved experiences for employees, customers, and their customers.

First gaining prominence with the Internet of Things (IoT) a few years back IBM defined edge computing as a distributed computing framework that brings enterprise applications closer to where data is created and often remains, where it can be processed. This is where decisions are made and actions taken.

5G stands for the Fifth Generation of cellular wireless technology. Beyond higher speed and reduced latency, 5G standards will have a much higher connection density, allowing networks to handle greater numbers of connected devices combined with network slicing to isolate and protect designated applications.

Today, 10% of data is processed at the edge, an amount IBM expects to grow to 75% by 2025. Specifically, edge computing enables:

• Better data control and lower costs by minimizing data transport to central hubs and reducing vulnerabilities and costs
• Faster insights and actions by tapping into more sources of data and processing that data there, at the edge
• Continuous operations by enabling systems that run autonomously, reduce disruption, and lower costs because data can be processed by the devices themselves on the spot and where decisions can be made

In short: the growing number of increasingly capable devices, faster 5G processing, and the increased pressure to drive the edge computing market beyond what the initial IoT proponents, who didn’t have 5G yet, envisioned. They also weren’t in a position to imagine the growth in the processing capabilities of edge devices in just the past year or two.

But that is starting to happen now, according to IDC: By 2023, half of the newly deployed on-premises infrastructure will be in critical edge locations rather than corporate datacenters, up from less than 10% today.

Also unimagined was the emergence of the hybrid multicloud, which IBM has only recently started to tout. The convergence of 5G, edge computing, and hybrid multicloud, according to the company, is redefining how businesses operate. As more embrace 5G and edge, the ability to modernize networks to take advantage of the edge opportunity is only now feasible. 

And all of this could play very well with the new z machines, the z15 T02  and LinuxONE lll LT2. These appear to be sufficiently capable to handle the scale of business edge strategies and hybrid cloud requirements for now. Or the enterprise class z15 if you need more horsepower.

By moving to a hybrid multicloud model, telcos can process data at both the core and network edge across multiple clouds, perform cognitive operations and make it easier to introduce and manage differentiated digital services. As 5G matures it will become the network technology that underpins the delivery of these services. 

Enterprises adopting a hybrid multicloud model that extends from corporate data centers (or public and private clouds) to the edge is critical to unlock new connected experiences. By extending cloud computing to the edge, enterprises can perform AI/analytics faster, run enterprise apps to reduce impacts from intermittent connectivity, and minimize data transport to central hubs for cost efficiency. 

Deploying a hybrid multicloud model from corporate data centers to the edge is central to capitalizing on  new connected experiences. By extending cloud computing to the edge, organizations can run AI/analytics faster  while minimizing data transport to central hubs for cost efficiency. By 2023, half of the newly deployed on-premises infrastructure will be in critical edge locations rather than corporate datacenters, up from less than 10% today. It’s time to start thinking about making edge part of your computer strategy. 

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

Mayflower Autonomous Ship

Growing up in Massachusetts, DancingDinosaur was steadily inundated with historical milestones: the Boston Massacre, Pilgrims landing at Plymouth Rock, we even had a special school holiday, Evacuation Day. It is only celebrated in Boston, to commemorate the day the colonials forced the British out of Boston. This year commemorates the 400th anniversary of the Mayflower’s arrival, which evolved into Thanksgiving and subsequently turned into a great day for high school football games.

IBM took the occasion as an  opportunity to build a completely autonomous ship and sail it from England to Massachusetts unmanned to mark that  anniversary, September 2020. The project , dubbed the Mayflower Autonomous Ship  (MAS) was launched as an occasion for IBM to introduce IBM Edge Computing in a dramatic way.

IBM defines edge computing as decentralized data and application processing across hundreds to millions of endpoints residing outside of a traditional datacenter or public cloud. MAS relies on IBM’s Edge Computing

“You take the human factor out of ships and it allows you to completely reimagine the design. You can focus purely on the mechanics and function of the ship,” writes Brett Phaneuf, Managing Director of MAS. The idea was to create an autonomous and crewless vessel that would cross the Atlantic, tracing the route of the original 1620 Mayflower and performing vital research along the way.

For MAS to survive the voyage, he continued,  the team opted for a trimaran design, which is both hydro- and aero-dynamic Using aluminum and composite materials, MAS will be lightweight, about 5 tons and 15 meters in length. That’s half the length and less than 3 percent of the weight of the original Mayflower, which took almost two months for a voyage that the MAS team planned to complete in less than two weeks.

For power, MAS will use solar panels to charge on-board batteries, which will power MAS’s motor – even at night. A single wingsail will allow MAS to harness wind power as well as make it more visible to other ships. MAS will be able to clock speeds of around 20 knots, compared to the original Mayflower’s 2.5 knots.

When it comes to modern technologies, the original Mayflower used a ship’s compass for navigation. To measure speed, it towed a ‘log-line’ – a wooden board attached to a hemp line with knots tied in it at uniform intervals (hence the term ‘knots’ still used to measure a ship’s speed today).

MAS, however, will have a state-of-the-art inertial navigation and precision GNSS positioning system. It will have a full suite of the latest oceanographic and meteorological instruments, a satellite communications system, and 2D LIDAR and RADAR sensors.

With no crew on board, MAS needs to make its own decisions at sea. MAS’ mission control system will be built on IBM Power Systems servers. MAS is currently using real data from Plymouth Sound to train IBM PowerAI Vision technology to recognize ships, debris, whales and other hazards which come into view on MAS’s on-board video cameras.

When a hazard is detected, MAS will use IBM Operational Decision Manager software to decide what to do. It may change course, or, in case of emergencies, speed out of the way by drawing additional power from its on-board back-up generator. Connectivity in the middle of the Atlantic is patchy, so MAS will use edge devices on board to store and process data locally when need be. Every time it gets  a connection, the ship will connect to the IBM Cloud and put the systems back into sync.

MAS will carry three research pods that carry scientific instrumentation to ensure scientists can gather the data they need to understand and protect the ocean, especially in the face of threats from pollution and global warming.

By leveraging AI, machine learning, and other new technologies IBM hopes it will start a new era of marine exploration. Through the University of Birmingham’s Human Interface Technologies Team, MAS plans to open the experience of the mission to millions of other ‘virtual pilgrims’ around the world via a mixed reality experience that uses the latest Virtual and Augmented Reality technologies. Bon Voyage!

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/