Remote Access Appliance Complex Event Processing Bandwidth Reduction
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Solution Overview
Problem
Modern data centers face challenges in efficiently managing and analyzing the vast amount of data from various sensors, leading to bandwidth issues due to the need to transmit all data points in real-time, which is unsustainable in large-scale environments.
Innovation Solution
A method using a remote access appliance with a complex event processing subsystem to analyze data and generate event-related signals, which are then transmitted through a service bus proxy subsystem to separate messaging queues for high and non-high priority events, allowing for efficient data aggregation and storage, reducing the bandwidth required for data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensor data points are transmitted in real-time to users and applications, then complete monitoring information is provided, but network bandwidth is significantly consumed
Solution Approach 1:
The patent extracts only the essential and relevant information from the vast sensor data through intelligent agents that analyze data locally and extract key events, trends, and anomalies. This extracted information is then transmitted to users, eliminating the need to send all raw data points while maintaining monitoring effectiveness and reducing bandwidth consumption.
Solution Approach 2:
The patent introduces intelligent agents as intermediary components between sensors and users/applications. These agents act as mediators that collect, analyze, and filter sensor data locally, transforming raw data into meaningful information before transmission. This intermediary layer prevents direct transmission of all data points, significantly reducing network bandwidth usage while preserving essential monitoring information.
2Speed
If data from hundreds or more sensors is collected and transmitted every second, then real-time monitoring capability is achieved, but the complexity of data management increases
Solution Approach 1:
The patent segments the data management function by deploying distributed intelligent agents at different locations within the data center infrastructure. Each agent is responsible for monitoring specific sensors and devices locally, dividing the overall data management task into manageable segments. This segmentation maintains real-time monitoring capability while reducing the complexity burden on any single system component.
Solution Approach 2:
The patent implements self-service through autonomous intelligent agents that automatically collect, analyze, and manage their local sensor data without requiring centralized processing of every data point. These agents independently perform data filtering, event detection, and local decision-making, enabling real-time monitoring while significantly reducing the complexity of centralized data management.
Data Source
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AI summary
A method is disclosed for forming a distributed data store using a remote access appliance associated with a data center infrastructure management (DCIM) system. Data may be generated which is associated with operation of managed device being monitored by the DCIM system. At least one remote access appliance may be used to receive the data. An element library framework may be used by the remote access appliance to generate events from the data. The remote access appliance may also be used to implement a complex event processing subsystem to analyze the events and to generate event related signals therefrom. A bus may be used to transmit the event related signals from the appliance to a common platform services (CPS) subsystem of the DCIM system. The CPS subsystem may be used to receive the event related signals and to use the event related signals to inform the user of an aspect of performance of the managed device.