IoT Communication Channel Selection via Dynamic Weighting
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Solution Overview
Problem
IoT devices face challenges in dynamically selecting the most appropriate communication channel for data transmission based on real-time network conditions, often prioritizing speed over cost and power efficiency, leading to inefficient data transmission.
Innovation Solution
A system and method that analyze communication requests, retrieve factors like cost, latency, and power usage, and apply weights to select the optimal communication channel for IoT devices, using software-defined radios to switch between cellular and satellite channels based on priority factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a particular communication channel is selected based on speed, then data transmission time is reduced, but transmission cost and power consumption increase
Solution Approach 1:
The system dynamically adjusts communication channel selection based on real-time conditions. The channel selector evaluates multiple factors including cost, latency, throughput, and power usage, then applies weights to these factors to determine the optimal channel for each communication request. This dynamic adaptation allows the system to balance speed requirements against power consumption and cost constraints.
Solution Approach 2:
The system changes operational parameters by adjusting the weights assigned to different evaluation factors. Based on the preliminary analysis of communication requests and current network conditions, the system modifies the importance (weights) of cost, latency, throughput, and power usage parameters. This allows flexible optimization where speed-critical transmissions can use faster but more power-intensive channels, while non-urgent transmissions use more efficient channels.
2Loss of time
If a particular communication channel is selected based on speed, then data transmission time is reduced, but transmission cost increases
Solution Approach 1:
The channel selection process dynamically adapts to each communication request by performing preliminary analysis and adjusting channel weights in real-time. This allows the system to select faster, more expensive channels when time is critical, and slower, cheaper channels when cost is the primary constraint, optimizing the trade-off between transmission time and cost.
Solution Approach 2:
The system modifies the weighting parameters for cost and latency based on the characteristics of each communication request. By changing these parameters dynamically, the system can prioritize speed reduction when necessary while minimizing cost increases, and vice versa, achieving optimal balance between transmission time loss and cost loss.
3Adaptability or versatility
If multiple communication channels are available for selection, then adaptability to different network conditions is improved, but system complexity increases
Solution Approach 1:
The channel selector is designed as a universal component that handles multiple communication channels (cellular, satellite, etc.) through a single integrated system. It performs multiple functions including retrieving network conditions, evaluating communication requests, applying weighted factors, and selecting optimal channels. This multi-functional design provides high adaptability while managing complexity through consolidation.
Solution Approach 2:
The channel selector acts as an intermediary layer between the communication system and multiple available channels. It abstracts the complexity of channel management by providing a unified interface that evaluates all channels against weighted criteria and automatically selects the optimal one, shielding the rest of the system from channel-specific complexities while maintaining high adaptability.
Data Source
AI summary
A method and system of transmitting data. The method comprises receiving data, in a memory of the server computing device, from an asset tracker device; determining, in a processor of the server computing device, one or more weighting factors representing a respective priority associated with one or more of a latency, a cost, a power utilization and a throughput associated with transmission of the data for each of a plurality of communication channels; and selecting, from the plurality of communication channels, a communication channel for transmission of the data based at least in part on the one or more weighting factors and a transmission schedule for the data.