Wireless Sensor Network Topology Visualization with Concentric Circles
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Solution Overview
Problem
Existing wireless sensor network visualization software faces challenges in accurately displaying topology information for large networks with many nodes, often resulting in node duplication and difficulty in conveying accurate information.
Innovation Solution
A method and system that receive and compare node information from sensor nodes, compute visualization information for missing nodes, and display them on concentric circles, allowing for efficient visualization and automatic construction of topology without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor network observation software is used to display topology information, then node information can be visualized, but node duplication occurs and accurate information cannot be conveyed when the network includes many nodes
Solution Approach 1:
The patent segments the network topology display into hierarchical levels (cluster heads at upper levels, member nodes at lower levels) and spatial zones (concentric circles representing different distances from sink node). This segmentation prevents node duplication by organizing nodes into distinct visual categories and spatial regions, allowing accurate representation of large networks with many nodes.
Solution Approach 2:
The patent transforms the flat, two-dimensional node placement into a multi-dimensional visualization using concentric circles to represent radial distance from the sink node and angular positions to represent directional relationships. This dimensional transformation enables accurate display of topology information for large networks by adding spatial context that prevents node confusion and duplication.
2Ease of operation
If user manually arranges nodes in the network, then node positions can be controlled, but the process becomes complex and time-consuming when nodes are frequently added or modified
Solution Approach 1:
The patent implements self-service automation where the system automatically receives node information from sink nodes, computes visualization parameters (concentric circle level, angular position, radial distance) based on topology data, and renders the display without user intervention. This eliminates manual node arrangement operations and automatically adapts when nodes are added or modified, saving significant time and effort.
Solution Approach 2:
The system performs preliminary computation of visualization parameters by pre-calculating the concentric circle level, angular position, and radial distance for each node based on its topology information before rendering. This preliminary action prepares the visualization data in advance, enabling rapid display updates when network topology changes without requiring manual re-arrangement.
3Loss of information
If traditional visualization methods are used, then simple networks can be displayed, but the topological structure becomes difficult to observe in large networks with many nodes
Solution Approach 1:
The patent segments the network topology into hierarchical levels (upper level for cluster heads, lower level for member nodes) and spatial zones (concentric circles representing distance bands from sink node). This segmentation preserves topological structure clarity in large networks by organizing nodes into distinct visual categories that maintain structural relationships even when node count is high.
Solution Approach 2:
The patent uses color differentiation to represent different node types (cluster heads versus member nodes) and potentially different topological roles. This visual encoding enhances the observability of topological structure in large networks by providing immediate visual cues about node hierarchy and relationships without requiring detailed inspection of each node.
Data Source
AI summary
A method, apparatus and system for displaying topology information of a wireless sensor network includes a plurality of sensor nodes. The method typically includes: receiving node information collected and extracted from the sensor nodes; comparing the received node information with stored node information; computing, when the received node information is unequal to the stored node information, visualization information on a sensor node whose information is not present in the stored node information; and displaying the sensor nodes on concentric circles using the visualization information.