Event-Based Data Management in Wireless Sensor Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data management approaches in wireless sensor networks, particularly those using relational database management systems, are not suitable for sensor nodes with limited resources such as power, memory, or processing capability.
Innovation Solution
A wireless sensor network architecture that employs an event-based data management model, utilizing discrete event operators and a publish/subscribe model, where sensor nodes communicate over wireless links to detect and transmit data related to discrete events of interest, optimizing query processing and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If relational database management systems are used for data management in wireless sensor networks, then data can be organized into tables with structured query capabilities, but the system becomes unsuitable for sensor nodes with limited resources such as power, memory, or processing capability
Solution Approach 1:
The patent extracts only the essential data management functionality needed for sensor networks, removing the overhead of full RDBMS systems. It implements a simplified event-based model that provides table-like data organization and query capabilities without the computational burden of relational database management, thereby reducing power consumption while maintaining ease of operation.
Solution Approach 2:
The patent changes the fundamental parameters of data management by transitioning from continuous relational database operations to discrete event-based processing. This parameter change reduces computational complexity and power consumption while preserving data organization and query capabilities through event-driven architecture and discrete event operators.
2Ease of operation
If relational database management systems are used for data management in wireless sensor networks, then data can be organized into tables with structured query capabilities, but the system consumes excessive memory and processing capability
Solution Approach 1:
The patent extracts only the necessary data organization features from RDBMS, implementing a simplified event-based model that provides table-like structures without the memory overhead of full relational database systems. This approach maintains data organization capabilities while significantly reducing memory consumption in resource-constrained sensor nodes.
Solution Approach 2:
The patent employs lightweight, disposable data structures and processing mechanisms that consume minimal memory. Instead of maintaining complex relational database structures in memory, the system uses simple event records and discrete event operators that can be processed and discarded, reducing overall memory usage while preserving data organization functionality.
3Ease of operation
If relational database management systems are used for data management in wireless sensor networks, then data can be organized into tables with structured query capabilities, but the system requires excessive processing capability
Solution Approach 1:
The patent extracts only the essential query processing functionality from RDBMS, implementing a simplified event-based query model that provides structured query capabilities without the processing overhead of relational database management. This approach maintains ease of query operation while significantly reducing processing power requirements through event-driven architecture.
Solution Approach 2:
The patent changes the processing model from continuous relational database operations to discrete event-based processing. This parameter change reduces computational complexity by processing data only when events occur, rather than continuously maintaining and querying relational structures, thereby reducing processing power requirements while preserving query capabilities.
4Productivity
If discrete event-based data management is implemented in wireless sensor networks, then resource usage is reduced and data retrieval efficiency is improved, but the system requires a different architectural approach from traditional RDBMS
Solution Approach 1:
The patent implements a self-service event-based architecture where sensor nodes autonomously generate and process events based on local conditions, eliminating the need for centralized RDBMS management. This self-service approach improves data retrieval efficiency by processing data at the source while using standardized event operators that simplify the overall system architecture despite the paradigm shift from traditional databases.
Data Source
AI summary
A wireless sensor network comprises a plurality of nodes that communicate over wireless communication links. At least one of the plurality of nodes receives sensor data from a sensor. At least one of the plurality of nodes determines when a discrete event occurs. When the discrete event occurs, transmits data related to the discrete event over at least one of the wireless communication links. The discrete event is a function of the sensor data.