IVR Edge Computing Latency Reduction
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Solution Overview
Problem
Existing interactive voice response (IVR) systems experience latency issues due to the distance between user equipment devices and the centralized storage of asset data, leading to longer response times from virtual agents compared to human agents, which can frustrate users and result in terminated interactions.
Innovation Solution
The system employs a distributed architecture that instantiates IVR application instances in both edge and core computing environments, utilizing network function virtualization (NFV) and network slicing to prioritize asset data and optimize data access, allowing virtual agents to respond more quickly by processing data closer to the user and dynamically selecting network slices for reduced latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If asset data is stored in centralized storage systems, then data management is simplified, but latency increases due to the distance between user equipment and storage systems
Solution Approach 1:
The patent segments the centralized storage system into distributed edge storage nodes deployed across multiple locations. Asset data is divided and stored in edge storage systems closer to user equipment, reducing access latency while maintaining simplified management through coordinated control mechanisms.
Solution Approach 2:
The patent introduces edge computing nodes as intermediaries between user equipment and centralized storage systems. These intermediaries cache asset data locally at edge locations, providing fast access while the centralized system maintains overall data management coordination.
2Stability of the object's composition
If virtual agents access asset data from centralized storage, then data consistency is maintained, but response time increases compared to human agents
Solution Approach 1:
The patent implements preliminary action by pre-caching frequently accessed asset data at edge storage nodes before it is needed. This allows virtual agents to retrieve data from local edge storage rather than waiting for centralized storage access, improving response speed while maintaining consistency through synchronization protocols.
Solution Approach 2:
The patent applies local quality by allowing different edge storage nodes to have locally optimized data copies tailored to their specific geographic regions and user bases. Each edge node maintains data consistency with the centralized system while providing locally optimized fast access for nearby users.
3Device complexity
If network resources are statically allocated, then network management is simplified, but latency cannot be optimized for different IVR sessions
Solution Approach 1:
The patent implements dynamic network resource allocation where network slices and bandwidth are automatically adjusted based on real-time IVR session requirements. The system dynamically provisions network resources to prioritize time-sensitive voice data transmission, reducing latency without requiring complex manual network management.
Solution Approach 2:
The patent changes network parameters dynamically based on session type and priority. Network slice selection, bandwidth allocation, and quality of service parameters are adjusted in real-time according to the specific IVR session requirements, optimizing latency for different scenarios while maintaining simplified overall network management through automated control.
Data Source
AI summary
Methods, computer program products, and systems are presented. The method, computer program products, and systems can include for instance: obtaining sensor output data from a user, wherein the sensor output data from the user includes voice data of the user; generating, during an interactive voice response session, vocal response data for presentment by a virtual agent to the user in response to the voice data, wherein the generating includes performing data access queries on one or more storage system; and prioritizing certain asset data of the one or more storage system, wherein the prioritizing is performed in dependence on data of the sensor output data.