Location-Aware Authentication Policy Provisioning for Low-Latency Handoffs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cloud-based authentication services experience significant latency when handling authentication requests from moving users as they transition between different service areas, leading to disruptions in service continuity.
Innovation Solution
Utilizing location data to predict user trajectories and proactively provide relevant policies and policy dependencies to new access points along the user's path, ensuring seamless authentication by bundling policies into container images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based authentication services process authentication requests in real-time for moving users, then authentication accuracy is maintained, but service latency increases significantly when users transition between service areas
Solution Approach 1:
The system performs preliminary actions by predicting user trajectories based on location data and proactively provisioning authentication policies to edge servers along the predicted path before users actually arrive. This advance preparation eliminates real-time processing delays when users transition between service areas, while maintaining authentication accuracy through pre-validation of policy applicability.
Solution Approach 2:
The authentication service is segmented into centralized policy management and distributed edge execution. The central system handles policy generation and trajectory prediction, while edge servers handle local authentication decisions. This segmentation allows real-time authentication at the edge without constant centralized communication, reducing latency for moving users.
2Reliability
If the system proactively provisions policies to multiple access points along user trajectories, then service continuity is improved, but system complexity increases
Solution Approach 1:
The trajectory prediction and policy provisioning system serves multiple access points simultaneously along predicted user paths. A single prediction engine generates policies for sequences of access points, making the system multi-functional rather than requiring separate processing for each access point. This reduces overall system complexity while improving service continuity.
Solution Approach 2:
Authentication policies are copied and cached at edge servers along predicted trajectories rather than being regenerated in real-time. This copying approach simplifies the system by eliminating redundant computation at each access point, while maintaining service continuity through local policy availability.
3Productivity
If authentication policies are bundled into container images for edge deployment, then processing speed increases, but deployment complexity increases
Solution Approach 1:
Authentication policies, configuration data, and execution environments are merged into unified container images for edge deployment. This combining approach increases processing speed by providing self-contained, pre-configured authentication modules that require minimal setup. The containerization framework manages the complexity, presenting a simplified interface for policy deployment across multiple edge servers.
Data Source
AI summary
Disclosed are apparatuses, systems, and techniques that improve efficiency and decrease latency of processing of authorization requests by cloud-based access servers that evaluate access rights to access various cloud-based services. The techniques include but are not limited to using location tracking data to predict that a user is to move from an area served by a first access point of the cloud-based services to an area served by a second access point of the cloud-based services. The techniques further include proactively providing policy data and policy dependencies to the second access point to minimize latency of processing of access requests generated by the user.