Sensor Network Transmission Control via Interest Zone Overlap
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Solution Overview
Problem
Conventional sensor networks experience unnecessary data transmissions due to predetermined transmission periods, leading to excessive power consumption, as they do not account for the periodicity and similarity of data, resulting in inefficient battery usage.
Innovation Solution
An apparatus and method that determine the number of data transmissions by detecting an interest zone based on user queries, calculating overlap with sensing zones, and adjusting transmission frequency accordingly, using geographical codes to assess overlap and aggregate only relevant data from nodes with overlapping sensing zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data transmission is performed at predetermined transmission periods, then data can be transmitted regularly and reliably, but unnecessary data transmissions occur and power is consumed unnecessarily
Solution Approach 1:
The transmission period is changed from a fixed predetermined value to a dynamic value that adjusts based on data periodicity and similarity characteristics. The system calculates the actual transmission period by analyzing data changes and sets the transmission period accordingly, allowing the transmission frequency to adapt to actual data variation needs rather than following a rigid schedule.
Solution Approach 2:
The system changes the transmission period parameter based on calculated data periodicity and similarity metrics. By computing these parameters from actual data and using them to adjust the transmission period, the system optimizes power consumption while maintaining reliable data transmission when changes occur.
2Productivity
If data transmission is performed at predetermined transmission periods, then regular data collection is maintained, but the periodicity and similarity of data to be transmitted are not considered
Solution Approach 1:
Instead of transmitting data at every predetermined interval, the system performs partial transmissions only when data periodicity or similarity thresholds are exceeded. This partial action approach avoids excessive transmissions while ensuring important data changes are captured, reducing energy loss without compromising data collection effectiveness.
Solution Approach 2:
The system implements feedback by calculating data periodicity and similarity metrics from transmitted data and using these calculations to adjust future transmission decisions. This closed-loop feedback mechanism enables the system to learn from actual data patterns and optimize transmission timing, reducing unnecessary transmissions while maintaining effective data collection.
3Reliability
If all sensor nodes transmit data at predetermined periods, then comprehensive data coverage is achieved, but the total number of data transmissions in the network increases
Solution Approach 1:
Each sensor node independently calculates its own data periodicity and similarity characteristics and determines its transmission schedule based on local data conditions. This local quality approach allows nodes with stable data patterns to reduce transmission frequency while nodes with significant changes maintain higher transmission rates, achieving comprehensive coverage with optimized overall network efficiency.
Data Source
AI summary
An apparatus and method of determining a number of data transmissions in a sensor network are provided. More particularly, an apparatus for determining a number of data transmissions preferably includes an interest zone detector for detecting an interest zone based on a user query, a zone determination unit for determining whether the interest zone is overlapped with a sensing zone, a zone calculator for calculating an overlap amount when the interest zone is overlapped with the sensing zone, and a transmission number determination unit for determining a number of data transmissions according to the overlap amount.