WAN Edge Computing Ideal for Managing IoT Data

In the next phase of the IoT, that will be heavily influenced by mobility, blockchain and WAN-edge optimization, most of the ‘things’ that enterprises care about will have to incorporate mechanisms for intelligence and control as well as adaptive connectivity. And these ‘things’ or smart devices will need to communicate with each other, at the edge, in addition to seamlessly connecting to a public or hybrid cloud.

And the more ‘things’ that are out there acting semi-autonomously in the wild, like drones, for example, the more they will need to operate effectively by being able to communicate with every other drone in the cluster, which in turn feeds edge computing devices that in turn feed cloud systems with aggregated performance metrics rather than raw data.

Adding “mobile” to the edge computing topology will also be significant for IoT. One of the key differentiators between 5G and earlier generations of cellular technology will be 5G’s ability to scale the loT. With 5G, the mobile network will be a key enabler for ‘things’ to be able to communicate with each other and not just centrally to the cloud or an operations center.

Hybrid/Multi-Cloud imperatives will also have an impact to IoT, given that most enterprises are still moving workloads to the cloud (primarily Amazon, Microsoft and Google), so while demand for cloud services is still growing, cloud providers cannot grow if they run out of datacenter space. Thus, their edge presence will be defined and driven by data requirements for latency, data criticality and data volume.

There are some key multi-cloud and hybrid-WAN use cases that we can expect to emerge, such as dynamic application movement based on performance or cloud-bursting for incremental workloads. Enterprises are typically looking to accomplish several strategic objectives with hybrid/multi-cloud:

  • Risk mitigation: reduce exposure to large, sensitive data sets in private clouds
  • Optimization of existing on-premises investments: cloud-first approach for net-new workloads/projects
  • Division of labor: public cloud/off-premises deployment for workloads with distributed user bases; incorporate ‘digital labor’ wherever practical
  • Lifecycle management: public clouds for test/dev in the cloud; private clouds for live production

What about managing and analyzing the industrial things or IIoT? IIoT was initially introduced to manufacturing through CNC machines, air compressors and HVAC equipment. Now, manufacturers are taking advantage of IIoT benefits in tools and machinery, equipped with sensors and actuators to further improve manufacturing operations.

Manufacturing companies use private networks for performance monitoring and controlling machinery. Versa SD-WAN allows network admins in the manufacturing industry to establish unique policies to govern network traffic to prioritize data packets that ensure high priority frames are allowed to pass across the most efficient network paths.

Manufacturing companies use network segmentation as a way of separating and isolating individual product lines into sub-networks to provide security and improve performance. Suppliers could be compromised first, and they could spread the infection through sharing data with partners. SD-WAN allows segmentation of the network for both security and performance

With the advent of autonomous vehicles, the ability to host multiple WAN (radio) links will become essential for any SD-WAN solution.

SD-WAN also provides a centrally managed WAN-edge solution with enhanced security by delivering an unprecedented level of visibility into network and application activities at all WAN sites whether it’s a corporate data center or cloud environment. SD-WAN encrypts network data to disallow unauthorized access. Cloud and SaaS are changing the way manufacturers are deploying their networks, and many understand the important role networks play in our highly competitive global market. They understand that legacy networks can’t keep up with the demands of today’s real-time application consumption models.

The deluge of data that IoT devices generate could become a big target for malicious hackers looking to steal proprietary or personal data and so manufacturing companies will need to ensure that, not only is their SD-WAN suitable for deployment in their environment, but also that adequate security measures are fully embedded.

Autonomous vehicles will increase in significance in terms of ‘things’ that influence a network architecture transformation. In this respect, blockchain technology will likely prove useful for tracking and tracing authenticated vehicle or mobility data across platforms.

According to 451 Research, vehicles are becoming increasingly connected, evolving quickly from phone-tethering infotainment applications to providing safety and security, convenience, telemetry and tracking. Vehicles already generate massive amounts of data via sensors within and around them, which will only increase in the future with more widespread use of connected and autonomous vehicles. Once all the data that connected vehicles produce are shared and properly managed, opportunities for improved road safety, reduced congestion and optimal mobility behavior open up. From simple in-car applications to more complex vehicle-to-vehicle (V2V) cooperation systems and integrated mobility, services can be provisioned on demand by leveraging blockchain and WAN-edge functions alongside IoT, analytics and machine learning.