IoT Data Block Prioritization via Dynamic Weighting
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Solution Overview
Problem
Current IoT systems face challenges in efficiently prioritizing and transmitting large or complex data payloads across networks, where all fragments are treated equally, leading to inefficiencies and potential loss of important information due to equal priority levels, especially in scenarios where certain data fragments contain little useful information.
Innovation Solution
Implementing dynamic judicious weighting for data block prioritization in IoT networks, allowing for differential prioritization of packets or fragments based on their perceived information value, without human intervention, to optimize transmission efficiency and conserve resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If all data fragments are treated with equal priority levels, then transmission simplicity is maintained, but network efficiency deteriorates and important information may be lost
Solution Approach 1:
The patent applies local quality by assigning different priority levels to different data fragments based on their specific characteristics. Instead of uniform treatment, each fragment is evaluated and assigned a priority level (high, medium, low) based on factors like information value, fragment position, and reassembly requirements. This resolves the contradiction by improving network efficiency through differentiated prioritization while managing complexity through systematic classification rules.
Solution Approach 2:
The patent implements dynamic prioritization where priority levels are not fixed but determined dynamically based on fragment characteristics and network conditions. The system can adjust priority assignments in real-time based on factors such as fragment importance, current network congestion, and reassembly needs. This dynamic approach improves productivity by adapting to varying conditions while maintaining manageable complexity through predefined decision logic.
2Use of energy by moving object
If all data fragments are transmitted with equal priority, then transmission process is simple, but energy consumption increases due to unnecessary retransmissions
Solution Approach 1:
The patent reduces energy consumption by applying local quality to priority assignment - critical fragments receive high priority with guaranteed transmission, while less important fragments receive lower priority. This differential approach prevents wasteful retransmissions of non-critical data and focuses energy on delivering essential information, directly addressing the energy consumption issue while maintaining reasonable operational simplicity through automated classification.
Solution Approach 2:
The patent applies partial action by selectively prioritizing only the most important fragments rather than treating all fragments equally. High-priority fragments receive enhanced transmission resources and protection, while low-priority fragments use standard transmission. This partial prioritization strategy reduces overall energy consumption by avoiding excessive retransmission efforts on non-critical data while maintaining ease of operation through automated priority management.
3Productivity
If differential prioritization is implemented based on information value, then network capacity utilization improves, but system complexity increases
Solution Approach 1:
The patent improves network capacity utilization by applying local quality to fragment prioritization - different fragments receive different priority treatments based on their information value. Critical fragments (e.g., headers, important sensor data) are marked high-priority to ensure timely delivery, while redundant or less important fragments receive lower priority. This maximizes network capacity usage by ensuring bandwidth is allocated to the most valuable data, while system complexity is managed through clear classification criteria.
Solution Approach 2:
The patent changes the priority parameter dynamically based on fragment characteristics and network conditions. Instead of a fixed priority scheme, the system adjusts priority levels by evaluating multiple parameters including fragment position, information content, and network state. This parameter-based dynamic prioritization optimizes network capacity utilization while keeping the system manageable through systematic parameter evaluation and predefined priority assignment rules.
Data Source
AI summary
An IoT device Internet of Things (IoT) device including storage to store instructions and a processor to execute the stored instructions to prioritize data blocks of a data payload by dynamically assigning priority levels of the data blocks, and to transmit one or more of the data blocks based on the prioritizing.


