IoT Gateway Profiling Agent for Resource Bottleneck Detection
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Solution Overview
Problem
IoT gateways face performance bottlenecks due to limited hardware resources when processing and sending voluminous data to the cloud, and analyzing software and hardware logs to identify performance issues is a time-consuming and arduous task, often performed reactively.
Innovation Solution
A profiling agent is inserted into the IoT gateway to capture detailed gateway attributes such as CPU utilization, memory consumption, and latency profiles, which are then analyzed to identify resource-intensive processes, allowing for proactive optimization of hardware and software resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If log collection codes are stored within the IoT gateway, then logs can be collected locally, but the IoT gateway consumes additional memory resources
Solution Approach 1:
The patent extracts the log collection and analysis functionality from the IoT gateway by implementing a remote monitoring system that collects logs remotely and performs analysis externally, thereby reducing the memory burden on the gateway while maintaining reliable log collection capabilities
Solution Approach 2:
The patent introduces an intermediary monitoring system that acts as a bridge between the IoT gateway and the analysis process. This intermediary collects logs from the gateway, processes them remotely, and returns analysis results, thereby eliminating the need to store extensive log collection codes within the gateway's limited memory
2Measurement precision
If detailed log analysis is performed to identify performance issues, then root causes can be determined, but the analysis process becomes time-consuming and arduous
Solution Approach 1:
The patent implements preliminary action by continuously collecting and pre-processing logs in the background, maintaining ready-to-analyze log data and performance metrics. When performance issues arise, the analysis can immediately utilize pre-processed data, significantly reducing the time required for detailed analysis while maintaining high precision in identifying root causes
Solution Approach 2:
The patent establishes a feedback mechanism where the monitoring system continuously analyzes logs and provides real-time feedback on performance metrics. This automated feedback loop enables rapid identification of performance issues without requiring manual, time-consuming analysis, while maintaining high precision through systematic correlation of software and hardware log data
3Productivity
If reactive log analysis is performed only when performance issues are identified, then resource usage is reduced, but performance issues cause disruption before detection
Solution Approach 1:
The patent implements periodic action by establishing scheduled monitoring intervals where logs are automatically collected and analyzed at regular intervals. This proactive periodic monitoring detects performance issues before they cause significant disruption, while the monitoring intensity can be adjusted to optimize resource efficiency, balancing early detection with resource conservation
4Ease of manufacture
If software and hardware logs are collected separately, then collection processes are simple, but determining relationships between logs requires detailed and time-consuming analysis
Solution Approach 1:
The patent applies merging by integrating software log data and hardware log data into a unified monitoring framework that automatically correlates events across both log types. This combination maintains the simplicity of separate collection processes while eliminating the complexity of manual correlation analysis through automated timestamp-based matching and event linkage algorithms
Data Source
AI summary
Various embodiments of systems and methods for monitoring IoT gateways are described herein. The method includes rendering an option to operate an internet of things (IoT) gateway in one of a profile and a normal mode. When the profile mode is selected, a profiling agent is attached to the IoT gateway to captured one or more gateway attributes indicative of performance of at least one of a software application and one or more processes executing within the software application of the IoT gateway. The captured gateway attributes are sent to a server or cloud for further analysis and processing, e.g., to improve software application executing within the IoT gateway to enhance the performance of the IoT gateway. When the normal mode is selected, a program to capture one or more hardware attributes of the IoT gateway is executed to capture hardware attributes to analyze the performance of the IoT gateway.