Dynamic Functionality Partitioning in Sensor Networks
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Solution Overview
Problem
Existing systems lack dynamic partitioning of functionality between remote sensor nodes and central processing subsystems, which are sub-optimal due to varying environmental conditions such as power, thermal, and communication bandwidth, leading to inefficient data preprocessing and communication requirements.
Innovation Solution
Implementing a system that dynamically allocates functionality between remote sensor nodes and a processing subsystem based on available communication capabilities, allowing each node to determine the optimal location for executing specific functions, thereby adjusting preprocessing and communication strategies in response to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static functionality partitioning is used between remote sensors and central processing subsystem, then system design is simplified, but system performance becomes sub-optimal under varying environmental conditions
Solution Approach 1:
The patent implements dynamic functionality partitioning where the processing subsystem and sensor nodes continuously negotiate and adjust the division of computational tasks based on real-time communication capabilities, power availability, and thermal conditions. This allows the system to transition from static to dynamic operation, optimizing performance under varying environmental conditions while maintaining manageable complexity through automated negotiation protocols.
Solution Approach 2:
The system dynamically changes operational parameters including data preprocessing extent, communication bandwidth allocation, power consumption levels, and thermal management strategies based on environmental conditions. By adjusting these parameters in real-time, the system achieves optimal performance across diverse operating scenarios without requiring complex manual reconfiguration.
2Quantity of substance
If data preprocessing is performed at remote sensor nodes, then communication bandwidth requirements are reduced, but power consumption and computational load at sensor nodes increase
Solution Approach 1:
The patent implements dynamic negotiation between sensor nodes and the processing subsystem to adjust the extent of data preprocessing based on real-time power availability and communication bandwidth conditions. When power is abundant and bandwidth constrained, more preprocessing occurs at sensor nodes. When power is limited, preprocessing is reduced and more raw data is transmitted. This dynamic balance optimizes both bandwidth utilization and power consumption.
Solution Approach 2:
The system dynamically adjusts preprocessing parameters such as data compression level, feature extraction depth, and data sampling rate at sensor nodes based on available power and communication conditions. This allows flexible optimization of the trade-off between reducing communication bandwidth requirements and managing power consumption at remote nodes.
3Device complexity
If more functionality is allocated to central processing subsystem, then sensor node complexity is reduced, but communication requirements and central subsystem load increase
Solution Approach 1:
The patent implements dynamic functionality allocation where sensor nodes and the central processing subsystem continuously negotiate the division of computational tasks based on real-time communication capabilities and processing loads. This dynamic adjustment allows the system to optimize the balance between sensor node complexity and communication requirements, transitioning functionality allocation based on operational conditions without manual intervention.
4Adaptability or versatility
If dynamic functionality partitioning is implemented, then system adaptability to environmental conditions is improved, but system complexity and coordination overhead increase
Solution Approach 1:
The patent implements a universal negotiation framework that enables sensor nodes and the processing subsystem to dynamically allocate functionality based on multiple environmental factors including power availability, thermal conditions, and communication bandwidth. This multi-functional negotiation protocol provides a standardized mechanism for adapting to various operational scenarios while maintaining systematic coordination through established communication interfaces and decision-making algorithms.
Data Source
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AI summary
A sensor and processing system dynamically partitions functionality between various remote sensor nodes and a processing subsystem based on available communication capabilities. Redundant functionality is located at the processing subsystem and each of the various remote sensor nodes, and each sensor node coordinates with the processing subsystem to determine the location (e.g., at the processing subsystem or at the sensor node) at which a particular functionality is executed.