Sensor Hub Offloading Processor Tasks
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Solution Overview
Problem
The increasing complexity of sensor data from multiple sensors in electronic devices poses challenges in power management and processing efficiency, particularly due to power-hungry host processors and battery limitations, which existing offloading technologies struggle to address effectively.
Innovation Solution
A system that dynamically learns device operation to offload processing tasks from a host processor to a sensor hub using a feedback-based configuration, allowing for bi-directional offloading and on-loading operations without affecting sensor hub functionality, and utilizes machine learning to make decisions based on sensor data and usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensor data processing is performed on the host processor, then processing capability is improved, but power consumption increases
Solution Approach 1:
The patent divides the processing system into two segments: the host processor and the sensor hub. The sensor hub is a separate processing unit specifically designed to handle sensor data, while the host processor focuses on higher-level application processing. This segmentation allows sensor data processing to be offloaded from the power-hungry host processor to the more energy-efficient sensor hub, thereby reducing overall power consumption while maintaining processing capability.
Solution Approach 2:
The sensor hub acts as an intermediary between the sensors and the host processor. It receives raw sensor data, performs initial processing and filtering, and then sends only the essential processed information to the host processor. This intermediary role reduces the processing burden on the host processor and enables more efficient power management by handling routine sensor processing in a lower-power component.
2Duration of action of stationary object
If sensor hub offloading is implemented, then battery lifetime is improved, but processing resources become constrained
Solution Approach 1:
The patent implements dynamic task management where the system can adaptively allocate processing tasks between the host processor and sensor hub based on current operational needs. The sensor hub can operate independently for routine sensor processing, but when more complex processing is required, tasks can be dynamically transferred to the host processor. This dynamic allocation ensures that battery lifetime is extended through offloading while maintaining access to full processing resources when needed.
Solution Approach 2:
The sensor hub performs preliminary processing of sensor data before it reaches the host processor. It filters, aggregates, and pre-processes sensor information, so that when data is transferred to the host processor, it is already in a more manageable format. This preliminary action reduces the processing burden on the host processor and allows the system to maintain extended battery life while still providing access to full processing capabilities when required.
3Productivity
If dynamic task allocation is used, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent employs feedback mechanisms where the sensor hub and host processor continuously monitor each other's workload and performance. Based on this feedback, tasks are dynamically allocated to the appropriate processor. The sensor hub can detect when it needs additional processing power and request assistance from the host processor, or the host processor can monitor sensor hub performance and proactively transfer tasks. This feedback-driven approach enables efficient dynamic task allocation while keeping the control logic relatively simple and manageable.
Data Source
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AI summary
Technologies for transferring offloading or on-loading data or tasks between a processor and a coprocessor include a computing device having a processor and a sensor hub that includes a coprocessor. The coprocessor receives sensor data associated with one or more sensors and detects events associated with the sensor data. The coprocessor determines frequency, resource usage cost, and power state transition cost for the events. In response to an offloaded task request from the processor, the coprocessor determines an aggregate load value based on the frequency, resource usage cost, and power state transition cost, and determines whether to accept the offloaded task request based on the aggregate load value. The aggregate load value may be determined as an exponential moving average. The coprocessor may determine whether to accept the offloaded task request based on a principal component analysis of the events. Other embodiments are described and claimed.