Sensor Data Stream Allocation for Load-Balanced Processing

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Solution Overview

Problem

Existing systems face inefficiencies in processing sensor data streams due to improper distribution, leading to interruptions and inefficiencies in processing, particularly caused by noise data and varying data loads, which can result in suboptimal server load management.

Innovation Solution

A system that includes a data collection unit for receiving sensor data streams, an allocation unit for dynamically allocating terminal devices to suitable data collection units based on status information and load monitoring, and a postprocessing unit for filtering and compressing noise data, using prediction and pattern analysis to optimize data processing and transmission.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If sensor data streams are transmitted in real time from multiple terminal devices, then the system can monitor production facilities and health conditions effectively, but the data volume increases significantly causing processing interruptions and inefficiencies

Engineering Contradiction:

Improvemonitoring reliabilityVSAvoiddata processing efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system segments incoming sensor data streams into different processing queues based on data type, priority, and source. High-priority monitoring data is separated from routine sensor data, allowing critical monitoring functions to be processed reliably while managing overall system throughput efficiently.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

An intermediary data buffering and preprocessing layer is introduced between sensor data collection and main processing systems. This buffer absorbs data volume fluctuations, preventing processing interruptions while maintaining real-time monitoring capabilities through selective data prioritization.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If all sensor data is processed without filtering, then complete data is available for analysis, but noise data reduces processing efficiency and increases system load

Engineering Contradiction:

Improvedata completenessVSAvoidprocessing speed

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The system extracts and removes noise data and redundant information from sensor streams using filtering algorithms. By taking out harmful noise components while preserving valid sensor data, the system maintains data completeness for analysis while significantly improving processing speed and reducing system load.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Different filtering strategies are applied to different portions of the data stream based on local characteristics. Critical monitoring data receives minimal filtering to preserve completeness, while routine sensor data undergoes aggressive noise filtering to maximize processing efficiency.

Inventive Principle:

Principle #3Local quality

3Productivity

If data is distributed to multiple servers, then processing capacity increases, but improper distribution causes load imbalance and processing interruptions

Engineering Contradiction:

Improveprocessing capacityVSAvoidprocessing continuity

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements feedback-based dynamic load balancing that continuously monitors server status and adjusts data distribution in real time. When a server becomes overloaded, the feedback mechanism redirects subsequent data streams to underutilized servers, maintaining processing continuity and preventing interruptions while utilizing full system capacity.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Data distribution is made dynamic rather than static, with the system adapting server allocation based on real-time conditions. Processing capacity is optimized by dynamically assigning data streams to servers with available resources, ensuring both high productivity and continuous processing without interruptions.

Inventive Principle:

Principle #15Dynamics

4Loss of information

If sensor data streams include noise and redundant data, then all detected information is captured, but transmission and processing efficiency decrease

Engineering Contradiction:

Improveinformation captureVSAvoidtransmission time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system applies partial filtering by selectively removing only noise and redundant data while preserving all meaningful sensor information. This partial action approach maintains complete useful information capture while reducing transmission time by eliminating unnecessary data portions from the stream.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10613956B2Terminal device, system, and method for processing sensor data stream

Publication Date: 2020.04.07 SAMSUNG ELECTRONICS CO LTD

AI summary

A terminal device, a system, and a method for efficiently processing sensor data streams. The system for processing sensor data streams includes: at least one data collection unit for receiving the sensor data streams from at least one terminal device; and an allocation unit for monitoring a status of the at least one data collection unit, selecting one of the at least one data collection unit by using a monitoring result, and allocating the at least one terminal device to the selected data collection unit, wherein the at least one data collection unit receives the sensor data streams from the at least one terminal device allocated by the allocation unit.