Predictive Discovery Filtering for Edge Application Server Selection
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Solution Overview
Problem
Existing discovery procedures in network architectures, such as Edge Application Server (EAS) discovery, do not account for dynamic changes in network information, leading to sub-optimal communications and potential service disruptions due to rapid changes in the status of EASs and Application Clients (ACs, without considering future status predictions.
Innovation Solution
Leverage data analytics through an analytics service to obtain predictive information about discovery targets, enhancing the discovery procedure by filtering and selecting optimal targets based on future status, availability, and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If discovery procedures are based on current information of EASs and ACs, then the discovery process is simple and fast, but the discovery results become non-preferable or non-applicable soon after connection due to rapid changes in network status
Solution Approach 1:
The analytics service performs predictive analysis in advance to determine future status of EASs and ACs before the discovery procedure executes. This preliminary action provides forward-looking information that enables more reliable discovery decisions without complicating the actual discovery process flow.
Solution Approach 2:
An analytics service is introduced as an intermediary component between the discovery procedure and the network entities. This service collects data, performs predictive analysis, and provides enhanced discovery information back to the discovery procedure, isolating the complexity of analytics from the core discovery logic.
2Adaptability or versatility
If multiple discovery targets are identified through filtering, then more options are available for selection, but the difficulty of identifying the optimal choice increases without future status information
Solution Approach 1:
The analytics service provides feedback information about the future status, performance, and suitability of multiple discovery targets. This feedback enables the discovery procedure to not only identify multiple options but also to evaluate and select the optimal target based on predicted future conditions rather than just current state.
Solution Approach 2:
Predictive analytics are performed in advance to evaluate multiple discovery targets and determine their future suitability. This preliminary evaluation provides ranking or scoring information that simplifies the selection process among multiple targets by pre-identifying the most promising options based on future expectations.
3Reliability
If analytics service is integrated into discovery procedure, then predictive information is obtained for better target selection, but the overall system complexity and processing time increase
Solution Approach 1:
The analytics service performs predictive analysis in advance and maintains ready-to-use predictions for multiple entities. When a discovery procedure is triggered, the pre-computed analytics results can be quickly retrieved and applied, avoiding the need for real-time analysis and reducing the time overhead of integrating analytics into the discovery process.
Data Source
AI summary
Provided herein are methods for enhancing the existing discovery procedure by leveraging data analytics in the application and service enablement layer. For example, a method may comprise receiving, by an edge enabler server and from a user device, a first message indicating a discovery request for one or more discovery targets, sending, to an analytics service, a second message indicating a request for analytics information associated with the one or more discovery targets, wherein the analytics information comprises prediction information associated with a future status of the one or more discovery targets, receiving, from the analytics service, a third message comprising the analytics information associated with the one or more discovery targets, sending, to the user device and in response to the first message, a fourth message comprising a filtered list of discovery targets based on the analytics information associated with the one or more discovery targets.