Energy Cost Function Scheduling for Data Processing Apparatus
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Solution Overview
Problem
Data processing devices, especially those with limited resources like mobile and IoT devices, face challenges in optimizing energy efficiency due to the lack of effective scheduling methods that consider resource usage and energy costs, leading to inefficient operation and increased power consumption.
Innovation Solution
A method for scheduling operations in data processing apparatuses that determines an energy cost function for candidate schedules based on resource usage, allowing for the selection of schedules that minimize energy consumption by activating or deactivating resources efficiently, and considers factors like current resource state, activation/deactivation costs, and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If operations are scheduled without considering energy cost functions, then processing performance is maintained, but energy consumption increases
Solution Approach 1:
The patent changes the scheduling parameter from simple time-based or priority-based selection to energy cost function-based selection. The energy cost function evaluates multiple factors including activation energy, deactivation energy, and operational energy for each resource, enabling the scheduler to choose operation sequences that minimize total energy consumption while meeting processing requirements.
Solution Approach 2:
The patent performs preliminary calculation of energy cost functions for all candidate schedules before executing operations. By pre-evaluating the energy implications of different scheduling options and selecting the optimal schedule in advance, the system avoids energy-inefficient operations during runtime while maintaining processing performance.
2Productivity
If resources are activated frequently to handle operations, then processing capability is improved, but energy consumption increases
Solution Approach 1:
The patent merges operations that require the same resources into consolidated schedules, reducing the number of separate resource activations. By grouping operations that can share resource usage, the system minimizes activation/deactivation cycles while maintaining processing capability, thereby reducing energy consumption associated with resource management.
Solution Approach 2:
The patent implements dynamic scheduling that adapts resource activation based on operational requirements and energy cost calculations. Rather than continuously activating resources, the system dynamically determines when activation is necessary by evaluating energy cost functions, allowing resources to remain inactive when not needed while being activated only when operations require them.
3Use of energy by moving object
If resource activation and deactivation is optimized for energy efficiency, then energy consumption is reduced, but system complexity increases
Solution Approach 1:
The patent replaces complex mechanical resource management with a computational energy cost function evaluation system. Instead of using intricate hardware controls or complex scheduling algorithms, the system uses software-based energy cost calculations to determine optimal schedules, simplifying the overall system architecture while achieving energy efficiency goals.
Data Source
AI summary
A method of scheduling operations to be executed by a data processing apparatus 2 includes determining energy cost functions for candidate schedules of operations, based on which resources of the data processing apparatus are required for execution of the operations. One of the candidate schedules is selected based on the energy cost functions. By scheduling operations based on which resources are used by the operations, energy efficiency can be improved.