IoT Task Offloading Using Forecasted Surplus Energy Sharing
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Solution Overview
Problem
IoT systems face challenges in maintaining consistent operability due to battery drain in self-powered devices, particularly when energy harvesting varies significantly among devices, leading to labor-intensive battery replacements and inefficient energy use.
Innovation Solution
Implementing energy-harvesting capabilities in IoT devices and enabling them to forecast and share surplus energy within the network, allowing devices with energy deficits to off-load tasks to those with surplus energy, thereby reducing the need for battery replacements and optimizing energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If IoT devices are made self-powered with batteries, then device portability and deployment flexibility are improved, but battery replacement becomes labor-intensive and device operability becomes inconsistent
Solution Approach 1:
The system enables self-service through automated task off-loading. When a device detects insufficient energy, it automatically transfers tasks to other devices with sufficient energy based on forecast data exchange, eliminating the need for manual battery replacement and maintaining continuous operation
Solution Approach 2:
Devices perform preliminary energy forecasting and share forecast data with the network before energy depletion occurs. This advance planning allows the system to proactively redistribute tasks to devices with predicted surplus energy, preventing operational interruptions
2Duration of action of stationary object
If energy harvesting is implemented in IoT devices, then operational life is extended, but energy availability varies significantly between devices
Solution Approach 1:
The system merges energy resources across the device network by creating a shared energy pool through forecast data exchange. Devices with surplus energy effectively contribute to the collective system, allowing devices with varying harvesting capabilities to maintain reliable operation through resource pooling
Solution Approach 2:
Forecast data acts as an intermediary that mediates energy distribution decisions. By sharing predicted energy availability information, the system enables intelligent task routing to appropriate devices, balancing the varying energy harvesting capabilities across the network
3Productivity
If devices share forecast data frequently to enable task off-loading, then energy utilization efficiency is improved, but overhead communication increases
Solution Approach 1:
The system implements periodic forecast data exchange at optimized intervals rather than continuous communication. Devices share forecast information at scheduled times, maintaining energy utilization efficiency while minimizing communication overhead and energy consumption
Solution Approach 2:
The system uses partial action by exchanging only essential forecast data elements needed for task off-loading decisions. This selective data sharing achieves sufficient energy optimization without the full overhead of comprehensive device state communication
Data Source
Figure 1~2B
Figure 3~4A
Figure 4B~4C
AI summary
A system comprises a plurality of network-connected processing devices, for example IoT devices. The respective processing device comprises processor circuitry configured to perform a processing task, a transceiver for communication with other processing devices in the system, and an energy harvesting device configured to provide energy for the processor circuitry and the transceiver. To improve utilization of harvested energy within the system by efficient off-loading of processing tasks between the processing devices, the processor circuitry is further configured to estimate (401) surplus energy in the processing device for an upcoming time period, and the transceiver is configured to transmit (403) forecast data representing the surplus energy to the other processing devices in the system.