Adaptive Thresholding for Sensor Bandwidth Allocation
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Solution Overview
Problem
Existing communication systems in distributed sensor networks face challenges in efficiently managing network traffic and congestion, particularly in allocating bandwidth and setting data detection thresholds, leading to suboptimal performance and wastage of bandwidth.
Innovation Solution
A system and method that dynamically allocates bandwidth by adjusting data sensor detection thresholds based on reallocated data rates, using a controller to set maximum and minimum sensitivities and reallocating excess capacity from underused channels to those needing it, while maintaining global sensitivity and meeting aggregate system-level link bandwidth constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If over-designing communication links to carry worst case traffic loads is used, then traffic congestion is avoided, but bandwidth is wasted and implementation costs increase
Solution Approach 1:
The system dynamically adjusts detection thresholds and data rates at sensor nodes based on real-time network conditions and congestion levels, allowing communication links to adapt their capacity usage rather than being statically over-designed for worst-case scenarios
Solution Approach 2:
The congestion control mechanism uses feedback from network conditions and sensor data characteristics to continuously optimize detection thresholds and data rates, enabling the system to achieve reliable congestion avoidance without permanently allocating excess bandwidth
2Loss of energy
If statistical multiplexing with a-priori allocated capacity is used, then bandwidth is efficiently utilized, but system performance deteriorates under actual traffic conditions due to limited accurate data
Solution Approach 1:
The system enables sensor nodes to self-adjust their detection thresholds and data generation rates based on local data characteristics and network feedback, eliminating the need for external controllers to have perfect knowledge of traffic conditions while maintaining efficient bandwidth utilization
Solution Approach 2:
The system changes detection threshold parameters dynamically based on observed traffic patterns and data characteristics, allowing the network to adapt to actual traffic conditions rather than relying on pre-configured capacity allocations based on limited statistical data
3Measurement precision
If increasing sensor detection sensitivity is implemented, then more data is detected, but network congestion increases and bandwidth is overwhelmed
Solution Approach 1:
The system applies different detection thresholds and data rates to different sensor nodes and data channels based on local data characteristics and network conditions, allowing high sensitivity where needed while maintaining overall network efficiency through localized optimization
Solution Approach 2:
The system dynamically changes detection threshold parameters at sensor nodes based on network congestion levels and data characteristics, enabling high detection sensitivity when bandwidth is available while reducing sensitivity thresholds when network capacity is constrained
Data Source
Figure 1A~1B
Figure 2A~2B
Figure 2C~2D
AI summary
A system and method allocates bandwidth for a plurality of data sources within a communications network. The data sources each generate data and transmit the generated data along communications channels in a shared communications link of the communications network. Each data source includes a data sensor for sensing data generation at each data source indicative of network resource usage. A node is connected to the communications link for receiving the data generated from respective data sources. A controller is associated with at least one of the node and each data sensor and data source for establishing data sensor detection thresholds, reallocating excess data capacity from underused channels to those channels requiring excess data capacity, and setting new data detection thresholds for each data sensor based on reallocated data rates at each data source.