Cloud-based 5G security network architectures with intelligent steering
AssigneeZscaler, Inc.
InventorsNathan Howe, Kenneth B. Urquhart
Life of this patent
Estimating the term…
Abstract
Cloud-based 5G security, implemented in a Multi-Access Edge Compute (MEC) system, includes steps of receiving a request for a workload from User Equipment (UE); determining a type of traffic for the workflow and querying a machine learning engine based on the traffic type; informing the UE of how the workflow should be accessed; and receiving an updated request for the workflow and steering the traffic based on how the workflow should be steered. The steps can include receiving policy updates from a cloud-based system, related to how workloads should be steered.
Claims20
A method of cloud-based 5G security, implemented in a Multi-Access Edge Compute (MEC) system, comprising:
- receiving a request for a workload from User Equipment (UE);
- determining a type of traffic for the workflow and querying a machine learning engine based on the traffic type;
- informing the UE of how the workflow should be accessed;
- and
- receiving an updated request for the workflow and steering the traffic based on how the workflow should be steered.
A Multi-Access Edge Compute (MEC) system comprising:
- one or more servers each including at least one processor and memory storing instructions that, when executed, cause the at least one processor to
- receive a request for a workload from User Equipment (UE),
- determine a type of traffic for the workflow and querying a machine learning engine based on the traffic type,
- inform the UE of how the workflow should be accessed, and
- receive an updated request for the workflow and steer the traffic based on how the workflow should be steered.
A non-transitory computer-readable storage medium having computer-readable code stored thereon for programming a Multi-Access Edge Compute (MEC) system to perform steps of:
- receiving a request for a workload from User Equipment (UE);
- determining a type of traffic for the workflow and querying a machine learning engine based on the traffic type;
- informing the UE of how the workflow should be accessed;
- and
- receiving an updated request for the workflow and steering the traffic based on how the workflow should be steered.
Dependencies are inferred from the claim text.