Mobile Terminal Sensing Operation Processor Selection
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Solution Overview
Problem
Existing mobile terminal devices face challenges in selecting an appropriate processor for offloading sensing operations due to varying environmental conditions, leading to inefficient electricity consumption.
Innovation Solution
A sensing operation control method that involves receiving a request for sensing operations, specifying candidate processors for condition determination, calculating an evaluation value of electricity consumption based on event frequency, and selecting an optimal processor to perform condition determination, thereby reducing power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a processor performs condition determination for sensing operations, then electricity consumption is reduced, but the ability to appropriately select an offload processor varies depending on usage environment
Solution Approach 1:
The system pre-calculates and stores evaluation values representing electricity consumption for each processor under different sensing operation conditions. When a sensing operation request is received, the processor selection unit quickly retrieves and uses these pre-evaluated values to select the optimal processor, avoiding real-time complex calculations and enabling fast, environment-adaptive decisions
Solution Approach 2:
The system establishes a feedback mechanism where the actual electricity consumption and performance data from processor operations are collected and used to update the evaluation values. This allows the system to learn from actual usage patterns and continuously improve processor selection accuracy for different environmental conditions
2Adaptability or versatility
If multiple processors are installed for multi-functionalization, then device functionality is enhanced, but processor selection complexity increases
Solution Approach 1:
The processor selection unit autonomously evaluates candidate processors using pre-stored evaluation values and automatically selects the optimal processor without requiring manual intervention or complex external control. The system self-manages the complexity of multi-processor coordination by internalizing the selection logic
Solution Approach 2:
The system uses evaluation values as key parameters to simplify processor selection. Instead of considering multiple complex factors simultaneously, the selection is reduced to comparing numerical evaluation values that represent overall processor suitability, making the selection process manageable even with multiple processors
3Productivity
If condition determination is performed to reduce application program runtime, then productivity is improved, but electricity consumption calculation complexity increases
Solution Approach 1:
The system pre-calculates evaluation values representing electricity consumption for each processor under various sensing operation conditions and stores them in advance. This eliminates the need for complex real-time electricity consumption calculations when processor selection is needed, simplifying the decision-making process while maintaining accuracy
Solution Approach 2:
The system uses lightweight evaluation value data structures that are easy to store and retrieve, replacing complex real-time calculation models. These simplified data representations enable fast processor selection without requiring heavy computational resources
Data Source
AI summary
A mobile terminal device receives a request for a sensing operation from an application program, specifies candidate processors that are to perform condition determination to determine whether an event output from a sensor performing the sensing operation of the received request satisfies conditions for notification, the conditions being designated by the application program, calculates an evaluation value of electricity consumed by each of the candidate processors in the condition determination, using frequency of the event of the sensing operation of the received request in frequency data, the frequency data linking an event output from a sensor to frequency of generation of the event, and selects a candidate processor having an optimal evaluation value.