Sensor Data Aggregation with Multi-Dimensional Indexing
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Solution Overview
Problem
Sensor networks face challenges in efficiently aggregating, validating, and indexing sensor data from diverse sources, leading to issues with data redundancy, malicious data infiltration, and query scalability.
Innovation Solution
A method that includes deduplicating, validating, and formatting sensor data, generating metadata, and time-stamping it for indexing using a multi-dimensional array, with dimensions including time and pre-determined attributes, to facilitate efficient querying and communication within the sensor network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensor data is aggregated from multiple sources without deduplication, then data completeness is improved, but data redundancy increases
Solution Approach 1:
The patent applies preliminary action by performing deduplication operations before data aggregation and indexing. The system identifies and removes duplicate sensor readings at the aggregator level before forwarding data to the indexer, preventing redundant data from being stored in the multi-dimensional array. This preliminary filtering maintains data completeness while eliminating redundancy.
2Quantity of substance
If all sensor data is transmitted to the indexer without validation, then data volume is preserved, but malicious data infiltration increases
Solution Approach 1:
The patent implements preliminary validation at the aggregator node before data transmission to the indexer. The validation process checks sensor data for malicious patterns, anomalies, and integrity violations before allowing transmission. This preliminary security check maintains data volume preservation while blocking malicious data infiltration.
3Productivity
If sensor data is indexed without metadata generation, then indexing speed is improved, but query efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by generating metadata during the data aggregation phase before indexing occurs. The aggregator creates descriptive metadata including sensor identifiers, location information, and data characteristics, which are then used by the indexer to efficiently organize data in the multi-dimensional array. This preliminary metadata generation maintains indexing speed while significantly improving query efficiency.
4Productivity
If sensor data is not time-stamped during aggregation, then processing speed is improved, but temporal query accuracy deteriorates
Solution Approach 1:
The patent implements preliminary time-stamping at the aggregator node during data aggregation. Each sensor reading receives an accurate timestamp before being forwarded to the indexer, enabling precise temporal queries without requiring post-processing time synchronization. This preliminary time-stamping maintains processing speed while ensuring temporal query accuracy.
Data Source
AI summary
In particular embodiments, a method includes accessing sensor data from sensor nodes in a sensor network and aggregating the sensor data for communication to an indexer in the sensor network. The aggregation of the sensor data includes deduplicating the sensor data; validating the sensor data; formatting the sensor; generating metadata for the sensor data; and time-stamping the sensor data. The metadata identifies one or more pre-determined attributes of the sensor data. The method also includes communicating the aggregated sensor data to the indexer in the sensor network. The indexer is configured to index the aggregated sensor data according to a multi-dimensional array for querying of the aggregated sensor data along with other aggregated sensor data. One or more first ones of the dimensions of the multi-dimensional array include time and one or more second ones of the dimensions of the multi-dimensional include one or more of the pre-determined sensor-data attributes.