Distributed Sensor Network Server Architecture for Load Reduction
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Solution Overview
Problem
Conventional search engines are not suited for efficient retrieval of real-time information from a large number of sensors connected to a network, leading to server and network load bottlenecks when many mobile sensors are used.
Innovation Solution
A sensor network with distributed servers and a directory server that assigns home servers for each mobile sensor node, allowing for efficient data management and reduced load by transferring position and sensing data between servers based on node configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a centralized server is employed to track positions and collect sensor outputs, then users can easily retrieve positions when sensor positions are changed, but there could be bottlenecks in server processing and network traffic when the number of sensors is large
Solution Approach 1:
The patent divides the centralized server into multiple distributed servers, each managing a subset of sensor nodes. This segmentation distributes the processing load and data storage across multiple nodes, preventing bottlenecks while maintaining position tracking capabilities. Each distributed server handles local sensor data independently, reducing overall system load.
Solution Approach 2:
The patent introduces a hierarchical dimension to the system architecture by adding a directory server layer above the distributed servers. This directory server manages the mapping between sensor nodes and their home servers, enabling efficient position retrieval without requiring all sensors to communicate directly with a single centralized point, thus distributing load while maintaining ease of access.
2Ease of operation
If a centralized server is employed to track positions and collect sensor outputs, then users can easily retrieve positions when sensor positions are changed, but there could be bottlenecks in network traffic when the number of sensors is large
Solution Approach 1:
The network is segmented into multiple distributed server zones, each handling local sensor communications. This reduces the total network traffic on any single network segment, as sensors only need to communicate with their local home server rather than a centralized server, thereby reducing overall network load and energy consumption.
Solution Approach 2:
The directory server acts as an intermediary that manages the mapping between sensor nodes and their home servers. When position retrieval is needed, the directory server provides the appropriate home server information, allowing direct communication between the user and the relevant distributed server, thus reducing unnecessary network traffic through the centralized point.
3Productivity
If conventional search engines are used for retrieving real-time information from sensors, then data access is possible, but efficient retrieval of real-time information from large amounts of sensor information is not achieved
Solution Approach 1:
The system performs preliminary organization of sensor data by assigning each sensor node a home server and pre-establishing the mapping in the directory server. This preliminary structuring of data allows for direct and efficient retrieval of real-time information without requiring general search operations, significantly reducing retrieval time while maintaining data accessibility.
4Quantity of substance
If the number of mobile sensors is increased, then sensing coverage is improved, but data processing load and network traffic increase
Solution Approach 1:
The system segments the management of sensor nodes across multiple distributed servers, with each server independently managing its assigned sensors. This segmentation allows the system to scale to a large number of sensors without proportionally increasing the complexity of data management, as each distributed server handles its local subset independently.
Solution Approach 2:
The directory server serves as an intermediary that manages the global mapping between sensor nodes and their home servers. This intermediary structure enables the system to handle a large number of mobile sensors efficiently, as the directory server can provide appropriate home server information without requiring complex centralized processing for each sensor addition or movement.
Data Source
AI summary
To suppress a server processing load and a network load in a sensor network which accommodates a great number of mobile sensor nodes. Among a plurality of distributed data processing servers (DDS) for managing data of sensor nodes, a distributed data processing server (DDS) that is a home server to hold data of a mobile sensor node is set for each sensor node by a directory server (DRS). At each distributed data processing server (DDS), upon reception of the data from the sensor node, identification process is executed as to whether the data is sensor data to be managed by itself or another distributed data processing server. If a result of the identification is the sensor data to be managed by another distributed data processing server, the data is transferred to the distributed data processing server (DDS-1), which corresponds to the home server of the sensor data, based on setting of the directory server (DRS).