Network Concentrator Data Retrieval Scheduling
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Solution Overview
Problem
The existing data collection methods for M2M and IoT devices often lead to network congestion and resource wastage due to simultaneous data transmission requests exceeding the capacity of network concentrators, resulting in bottlenecks and extended device connectivity, which can shorten the lifespan of battery-powered devices.
Innovation Solution
A system where devices communicate with local network concentrators, and an information retrieval server manages data requests to limit the number of concurrent connections with each concentrator, ensuring data is retrieved efficiently by delaying requests until previous transmissions are completed, thus avoiding congestion and resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple devices simultaneously request data transmission through network concentrators, then data collection speed is improved, but network congestion increases and system resources are wasted
Solution Approach 1:
The system performs preliminary actions by obtaining information about device allocations and maximum concurrent communication limits for each network concentrator before initiating data requests. The information retrieval server schedules data requests to ensure that the number of concurrently communicating devices does not exceed the maximum capacity of any network concentrator, thereby preventing network congestion and resource waste before they occur.
2Reliability
If devices remain connected to the telecommunications network for longer periods to wait for data transmission, then data collection completeness is improved, but device battery life is reduced
Solution Approach 1:
The system implements feedback mechanisms where the information retrieval server continuously monitors and obtains updated information about device allocations to network concentrators and their maximum concurrent communication capacities. Based on this feedback, the server dynamically adjusts and reschedules data requests to optimize the balance between data collection completeness and energy consumption, ensuring devices remain connected only as long as necessary.
3Productivity
If the number of concurrent device connections to network concentrators is increased, then data retrieval efficiency is improved, but network bottlenecks occur
Solution Approach 1:
The system performs preliminary scheduling of data requests by obtaining information about device allocations and maximum concurrent communication limits for each network concentrator before initiating data collection. This advance planning allows the information retrieval server to optimize data retrieval efficiency while preventing network bottlenecks by ensuring the number of concurrent connections never exceeds network concentrator capacities.
Data Source
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AI summary
System and method comprising a plurality of devices configured to provide data. A plurality of network concentrators, wherein each network concentrator of the plurality of network concentrators is configured to communicate with a subset of the plurality of devices. A plurality of session management servers configured to retrieve data, obtained by any one or more of the plurality of devices, from the network concentrators. An information retrieval server configured to: obtain information describing the subset of devices allocated to each of the network concentrators and a maximum number of devices that each of the network concentrators can simultaneous communicate with and instruct the plurality of session management servers to request data from the plurality of devices by limiting requests for data from the devices such that the number of devices in communication with each network concentrator is at or below the maximum number.