Mobile Edge Computing, 5G

I posted the following on another thread just this morning, may have gotten lost or is it just too soon really. I know Saul, Bear, Bert, and others have taken a stake in FSLY. Peter Proffringa has a 20% stake per his most recent article.

I have 10% in FSLY and 5% in NET. One link given by a poster here, I need to give thanks to but can’t remember the name, brought me to this bit I’ve saved from a much more detailed report From Mobile Edge Computing, Mindshare. I am hoping that others here will find it compelling in as much as it will bring out some discussion on anticipated time lines in the roll out of 5G. Please forgive me, but let me know, if OT.

5G, IoT, and Edge Computing Data Services

MEC supported 5G networks will generate massive amounts of data. Data may be passed as a real-time stream to enterprise organizations for real-time decision making. In addition to conventional data analytics software, systems may be augmented with artificial intelligence to provide further data management efficiencies as well as improved decision making effectiveness.

In many cases, the data itself, and actionable information will be the product, often delivered in a Data as a Service (DaaS) market model. As the industrial IoT market in particular evolves, there will an increasingly large amount of unstructured machine data. This rapidly growing amount of machine generated industrial data will drive substantial opportunities for AI support of unstructured data analytics solutions.

Service providers must balance the need to determine what data may be processed at the edge (with potential real-time business implications) versus data that may be simply transmitted to a centralized cloud for storage and post-processing. The use of Artificial Intelligence (AI) for decision making in data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with MEC.

Data by itself is useless. Data needs to be managed and presented in a manner that is useful as information. DaaS represents a service model in which data is transformed into useful information.

A surprising number of enterprises entities, both current and prospective DaaS customers, do not realize they have options for combinations of data including (1) their own data, (2) other companies’ data, (3) public data, or a combination of all three. Accordingly, it was not surprising to find confusion even for many of those already considering Data as a Service, or already with DaaS in place.

Managed Edge Computing Data Services an Emerging Opportunity for MEC Infrastructure and Services Providers

One of the key opportunities for DaaS is enterprise data syndication, which is the opportunity for companies of various sizes to syndicate (e.g. share and monetize) their data. This is one of the biggest opportunities for MEC infrastructure and service providers and the DaaS market as whole.

However, there remain challenges above and beyond the core adoption barriers, which include specific security, privacy, and care of custody concerns.

Taking the aforementioned into account, Mind Commerce sees edge compute managed apps and services as an important area for edge computing infrastructure and services providers, which will include the following:

  • Managing app provisioning, administration, and operational control
  • Managing edge compute data including security/privacy and related access control
  • Managing syndication of enterprise and industrial customer data in a DaaS model

I hope you’ve found this as helpful as I did.