By Kurt Michel, SVP, Marketing, Veea
Intelligent systems have become an increasingly common part of everyday life. Using a combination of wireless communications networks, Internet of Things (IoT) sensors and devices, automation, artificial intelligence (AI), edge and fog computing and various other cutting-edge technologies and frameworks, providers are enhancing and improving both their operations and services.
IoT has quickly become one of the fastest growing areas across many industries, with the size of the current IoT market, including hardware, software, systems integration, and data services estimated at roughly $520 billion. The related AI technology market size is predicted to reach $267 billion by 2027, with 37 percent of businesses and organizations already employing it.
However, with technological advancements such as 5G and autonomous cars arriving daily, and a proposed national infrastructure bill possibly changing the infrastructure landscape, organizations across all sectors are constantly looking for ways to leverage their infrastructure to enable digital transformation of their businesses.
The solution they are looking for lies in technology improvements at the network edge.
Network edge computing adds computation capabilities at the edge of the network, improving application responsiveness while reducing data transport to core data centers. In this way, edge computing complements “cloud” processing in core datacenters
Edge technology adoption is quickly growing. According to a report by Grand View Research, the global edge computing market size is expected to reach $28.84 billion by 2025, with a CAGR of 54%.
The key to success at the network edge lies in improvements in connectivity, combined with processing resources that are in closer proximity to the devices that generate the data and use the processed results from that data. In fact, emerging innovative approaches combine connectivity and processing resources in the same extensible edge platforms that are built on Smart Edge Node (SEN) technology. This approach works especially well for logistics and large-scale manufacturing, as well as for the ever expanding Internet of Things (IoT) where sensors or data collecting devices are numerous and highly distributed.
Currently, the government is debating infrastructure investments that would “rebuild and reimagine the economy,” and edge network technology could certainly play a major role in the future of national infrastructure.
Edge networks offer a myriad of benefits that would optimize much of the national infrastructure.
To begin with, one of the most obvious advantages of processing-enabled edge networks is the increase in application performance and decision-making through reduced latency. Decision-making speed is absolutely vital to any company, and for businesses that provide data-driven services to customers, lagging application performance can frustrate customers and cause long-term damage to a brand. Since Smart Edge Nodes process IoT data locally, the information they collect doesn’t have to travel nearly as far as it would with a traditional cloud architecture – and application responsiveness in improved.
Another major impact edge-computing enabled “intelligent” networks can make in the national infrastructure push is in the development of autonomous vehicles Powerful enough to handle onboard computing tasks and well-connected enough to interface with multiple networks and devices, autonomous vehicles will be in constant communication with the world around them, making split-second decisions based upon the information flooding in from an array of sophisticated sensors.
Edge network technology will allow much of the data to be exchanged between the vehicles themselves, without requiring them to interface with distant cloud servers. This effectively turns every vehicle on the highway into an extension of every other vehicle’s sensors, effectively providing the very best information and decision-making possible in the highway environment.
Automobile makers must leverage edge computing technologies to address these ever-evolving challenges of handling, processing, and analyzing large amounts of data in order to make critical decisions quickly and efficiently. Estimates vary, but a single, self-driving test vehicle can produce a staggering 30 terabytes of data in a single day of driving, and much of this unstructured data will require powerful analytics software programs to produce the real-time decisions necessary for autonomous vehicles.
Intelligent Edge networks also offer improved scalability compared to enterprise data centers. As companies grow, they cannot always anticipate their IT infrastructure needs. Building a dedicated data center is an expensive proposition, which makes it even more difficult to plan for the future.
However, through the use of intelligent edge networks, expanding data collection and analysis no longer requires companies to erely solely on centralized, private data centers, which can be expensive to build, maintain, and expand. By combining colocation services with regional edge computing data centers, organizations can expand their intelligent edge network reach quickly and cost-effectively.
Computing, storage, and analytics capabilities are increasingly being combined into Smart Edge Node devices with smaller footprints that can be easily situated nearer to end-users. As local processing needs grow, the flexibility of leveraging an intelligent edge network’s capabilities allows organizations to adapt quickly to evolving markets and scale their data and computing needs more efficiently.
Finally, intelligent edge networks can also offer greatly improved cybersecurity, something that is critical in today’s cyber landscape for both organizations, and the country as a whole. As cyber threats continue to grow in both volume and sophistication, edge-processing-enhanced cybersecurity can be a powerful defensive tool. For example, a major concern with IoT devices is that they can be used as a point of entry for cyberattacks, allowing malware or other intrusions to infect a network from a single weak point. With appropriate, secure edge computing software, these malware-infected devices can be detected and “locked down” to prevent catastrophic damage.
While the proliferation of IoT edge computing devices does increase the overall attack surface for networks, it also provides some important security advantages.
Today’s traditional cloud computing architecture is centralized, which makes it especially vulnerable to distributed denial of service (DDoS) attacks and regional infrastructure failures. Intelligent edge networks distribute processing, storage, and applications across a wide range of devices and data centers, making it more difficult for any single disruption to take down the entire network.
Since more data is being processed on local devices rather than transmitting it over the Internet to a central data center, edge computing also reduces data exposure. There’s less data to be intercepted during transit, and even if a device is compromised, it will only contain the data it has collected locally rather than the trove of data that could be exposed by a compromised central server.
Shifting data processing to the edge of the network can help organizations take advantage of the growing number of IoT edge devices, improve network speeds, and enhance customer experiences. The scalable nature of intelligent edge networks also make them an ideal solution for fast-growing, agile companies. By harnessing the power of edge computing, companies can optimize their networks to provide flexible and reliable services that bolster their brand and keep customers happy.
Filed Under: IoT • IIoT • internet of things • Industry 4.0