Sensor Report Interval Arbitration for Multi-App Sampling Conflicts
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Solution Overview
Problem
Conflicts arise when multiple applications request sensor data from the same sensor at different intervals, leading to inefficiencies such as excessive resource and power use or inaccurate data provision, as existing solutions like oversampling or fixed report interval modes fail to accommodate varying requirements effectively.
Innovation Solution
Implementing multiple selectable report interval modes within the operating system, allowing applications to choose between strict, opportunistic, and automatic modes, enabling the sensor stack to arbitrate and provide data accordingly, thus optimizing power usage and data accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If oversampling is used to resolve conflicts between multiple applications requesting sensor data at different intervals, then data availability for all applications is improved, but power consumption and resource usage increase excessively
Solution Approach 1:
The system dynamically adjusts the sensor reporting interval based on the shortest requested interval among active applications. When applications are added or removed, the reporting interval is recalculated to match the new shortest interval, avoiding unnecessary oversampling. This dynamic adaptation resolves the contradiction by maintaining data availability while reducing power consumption when full oversampling is not needed.
Solution Approach 2:
The system changes the reporting interval parameter based on application requirements. Instead of using a fixed oversampling rate, the reporting interval is adjusted to match the shortest requested interval among active applications. This parameter change allows the system to provide accurate data to all applications without excessive power consumption associated with fixed oversampling.
2Measurement precision
If sensor data is provided at the shortest requested interval to all applications, then data freshness is improved, but applications that need less frequent data consume more resources than necessary
Solution Approach 1:
The system extracts only the necessary data subset for each application based on its specific interval requirements. Applications receiving data at longer intervals get fewer samples, while applications needing frequent data receive all samples. This extraction approach ensures data freshness for all applications without forcing unnecessary data transmission to applications that don't need frequent updates, thereby reducing energy waste.
Solution Approach 2:
Different quality levels of data delivery are provided to different applications based on their specific needs. Each application receives data at its requested interval rather than all applications receiving data at the shortest interval. This local quality differentiation maintains data freshness where needed while avoiding energy waste in applications that can tolerate less frequent updates.
3Device complexity
If fixed report interval mode is used, then system simplicity is maintained, but flexibility to accommodate varying application requirements is reduced
Solution Approach 1:
The system transitions from a fixed reporting interval to a dynamic one that automatically adapts to the shortest requested interval among active applications. This dynamic approach maintains system simplicity by using a single adaptive rule rather than multiple fixed modes, while simultaneously improving flexibility to accommodate varying application requirements as they are added or removed.
Data Source
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AI summary
A report interval mode is selected from one of multiple selectable report interval modes in cases where the preferred sensor sample intervals of multiple applications are different. By using multiple selectable report interval modes some of the problems that occur when a single fixed report interval mode is used can be avoided.