Dynamic Task Distribution for Energy-Constrained Mobile Sessions
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Solution Overview
Problem
High computational demands of services like AI for augmented reality or control, which require distribution across multiple devices, pose challenges due to limited computational power and energy consumption concerns on mobile terminals, making it difficult to provide efficient communication and computing services.
Innovation Solution
A method that involves receiving an energy consumption target and selecting a service provision profile to distribute tasks between a mobile terminal and other computing devices, ensuring the energy consumption target is met while meeting performance requirements, by optimizing the distribution of computational tasks and communication quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If computational tasks are distributed to cloud devices, then computational power is improved, but energy consumption and latency increase
Solution Approach 1:
The patent implements dynamic task distribution that adapts to changing energy conditions. The system monitors energy consumption targets and dynamically adjusts which tasks are executed locally versus offloaded to cloud devices, allowing the computational architecture to flex between local and distributed execution based on real-time energy constraints
Solution Approach 2:
The system changes the parameter of task execution location based on energy consumption targets. By evaluating whether to execute tasks locally or remotely based on energy constraints, the system optimizes the balance between computational power utilization and energy consumption, selecting the execution mode that best meets the energy target while maintaining service quality
2Power
If computational tasks are distributed to cloud devices, then computational power is improved, but service latency increases
Solution Approach 1:
The system dynamically determines task execution locations based on energy consumption targets and service requirements. By adapting the distribution strategy in real-time, the system can minimize latency for time-sensitive tasks while still utilizing cloud computing resources for less time-critical operations, thus balancing computational power gains with latency constraints
3Use of energy by moving object
If tasks are processed only on mobile terminal, then energy consumption is reduced, but computational power is insufficient
Solution Approach 1:
The patent segments computational tasks into local and remote components. Instead of processing all tasks uniformly, the system divides the workload and executes different segments on different devices based on energy consumption targets, allowing the mobile terminal to handle energy-efficient local tasks while offloading computationally intensive tasks to cloud devices
Solution Approach 2:
The system changes the execution parameter of tasks based on energy consumption targets. By evaluating energy constraints and adjusting the degree of task offloading accordingly, the system optimizes the balance between energy consumption and computational power, ensuring that energy-limited operations run locally while leveraging cloud power when energy permits
Data Source
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AI summary
According to various embodiments, a method for providing a communication and computing service session is described, comprising receiving an indication of an energy consumption target, selecting a service provision profile which specifies a distribution of tasks of the communication and computing service between the mobile terminal and one or more other computing devices, wherein, if it is determined that it is possible, the service provision profile is selected such that, when the mobile terminal and the one or more other computing devices perform computations as specified by the service provision profile, the energy consumption target is met and providing the communication and computing service session by distributing tasks of the communication and computing service to the mobile terminal and the one or more other computing devices in accordance with the selected service provision profile.