Cognitive Reliability Engine for Microservice Handoff
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Solution Overview
Problem
Reliability management in phone-hosted microservices is challenging due to the locomotive nature of mobile devices, as traditional reliability aspects from cloud web services cannot be directly applied, leading to potential service disruptions and delays during handoffs.
Innovation Solution
A cognitive reliability engine is connected to each mobile device to determine a reliability score through context and activity recognition, emitting beacons to other devices in the vicinity to manage handoffs, ensuring minimal delay and smooth service transitions by indicating availability or unavailability of hosted microservices based on predefined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile devices are used to host microservices, then service capabilities are extended beyond device limits, but service reliability deteriorates due to device mobility and unpredictable availability
Solution Approach 1:
The patent introduces a service broker as an intermediary component that mediates between microservice consumers and mobile device hosts. The broker maintains service registry information, manages service discovery, and handles failover logic, thereby insulating consumers from the unreliability of mobile hosts while preserving the ability to extend service capabilities across multiple devices.
Solution Approach 2:
The system performs preliminary actions by pre-registering microservices with the service broker before they are needed. The broker maintains advance knowledge of available services and their host devices, enabling proactive service discovery and failover preparation. This allows the system to respond quickly to device availability changes without disrupting service consumption.
2Stability of the object's composition
If traditional cloud web service reliability models are applied to mobile devices, then service consistency is maintained, but service disruptions occur due to device locomotion and network variability
Solution Approach 1:
The patent implements dynamic service registration and discovery mechanisms where the service broker continuously updates its registry based on current device availability. Mobile devices dynamically register and unregister services as they enter or leave the network, and consumers dynamically discover alternative hosts when primary hosts become unavailable. This dynamic adaptation maintains service continuity despite device mobility.
3Reliability
If manual delay is used in service handoffs, then service disruptions are reduced, but handoff delays increase
Solution Approach 1:
The service broker implements feedback mechanisms by continuously monitoring service host availability and proactively notifying consumers of upcoming service unavailability. When a mobile device indicates it will soon leave the network or become unavailable, the broker provides advance warning and coordinates automatic service migration to alternative hosts. This feedback-driven approach enables seamless handoffs without manual delays while maintaining service continuity.
Data Source
AI summary
Managing handoffs between a plurality of mobile devices in a phone hosted microservices architecture in a same vicinity, with each of the mobile devices connected to a cognitive reliability engine. The cognitive reliability engine, for each of the plurality of mobile devices hosting a hosted microservice, determining a reliability score for a time period through context and activity recognition of a user owning the mobile device. Depending on the reliability score, different beacons with data packets indicating that the microservice will end, the microservice may end, or the microservice will continue with surety for a specific time period.