Tiered Sensor Data Processing for Edge-Cloud Resource Management
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Solution Overview
Problem
As the number and types of sensors increase, there is a growing need for efficient data sorting and prioritization to manage the increasing amount of data and processing requirements, while also considering size and cost constraints in various devices.
Innovation Solution
Implementing a system where data from sensors is sorted and prioritized by a computing device, with some data processed locally for short-term decisions and other data transmitted to a cloud-computing device for medium to long-term processing and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If all sensor data is processed locally in individual devices, then response time for decisions is improved, but device complexity and processing power requirements increase significantly
Solution Approach 1:
The patent segments data processing into two distinct layers: local edge processing for time-critical decisions and cloud-based processing for non-time-critical analysis. The computing device in the vehicle handles only urgent sensor data locally, while transmitting other data to remote servers for processing, thereby dividing the computational burden between edge and cloud infrastructure.
Solution Approach 2:
The patent introduces a communication system as an intermediary layer between the vehicle's computing device and remote servers. This intermediary handles data transmission and routing, allowing the vehicle to offload processing tasks without direct constant connection to cloud infrastructure, thus reducing local processing requirements while maintaining response capabilities.
2Measurement precision
If more sensors are deployed to improve monitoring capabilities, then measurement precision and safety are improved, but data management complexity and processing requirements increase
Solution Approach 1:
The patent segments sensor data into different categories based on time-criticality and importance. Critical safety-related data from multiple sensors is processed locally with high priority, while non-critical data is aggregated and transmitted to cloud servers for batch processing, thereby managing the complexity introduced by multiple sensors through hierarchical data handling.
Solution Approach 2:
The patent applies partial processing locally and partial processing in the cloud rather than processing all data uniformly. By selectively processing only the most critical portions of sensor data locally and leaving other portions for cloud processing, the system manages data complexity from multiple sensors without requiring all processing to occur at the edge.
3Device complexity
If data is transmitted to cloud-computing devices for processing, then computational needs in individual devices are reduced, but data transmission time and network dependency increase
Solution Approach 1:
The patent segments data transmission based on priority and time-sensitivity. Time-critical data is processed locally without transmission delays, while non-time-critical data is transmitted to cloud servers for processing. This segmentation ensures that only necessary data undergoes transmission, minimizing time loss while still reducing computational needs for individual devices.
Solution Approach 2:
The patent implements preliminary local processing of sensor data before transmission to cloud servers. By pre-processing and filtering data at the edge device, the system reduces the volume of data requiring transmission and ensures that only processed, relevant information is sent to the cloud, thereby minimizing transmission time and network dependency.
Data Source
AI summary
Systems, methods, and apparatuses for data prioritization and selective data processing are described herein. A computing device may receive sensor data and prioritize a first portion of the sensor data over a second portion of the sensor data. The first portion of sensor data may be stored in a first memory that has a higher access rate than a second memory where the second portion of sensor data is stored. The first portion of sensor data may be processed with priority and the second portion of sensor data may be transmitted to a cloud computing device.