Application Grouping via Network Traffic Analysis
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Solution Overview
Problem
Network operators face challenges in accurately mapping and understanding the topology of complex computer networks, especially when migrating tasks to cloud environments, due to the dynamic nature of network infrastructure and security concerns with existing methods like trace route and software agents.
Innovation Solution
A method involving a software program with modules for discovering and classifying applications based on traffic flow and network statistics, creating a reference base and application glossaries, and automatically grouping applications for easier migration planning, using a computer-based apparatus with a processor and memory to analyze network devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods like trace route and software agents are used to map network topology, then network mapping can be performed, but security concerns arise and accuracy deteriorates in dynamic cloud environments
Solution Approach 1:
The patent introduces network traffic flow data as an intermediary medium to map network topology. Instead of using trace route or software agents that directly interact with network devices, the system analyzes existing traffic flow data between devices to infer network connections and topology, thereby avoiding security issues while maintaining mapping accuracy
Solution Approach 2:
The system creates a virtual copy of the network topology by analyzing traffic flow patterns. Rather than directly probing or agent-based discovery, it reconstructs the network map by copying and analyzing existing traffic data, which preserves security while enabling accurate topology discovery
2Loss of energy
If cloud services are used to avoid capital expenditures, then cost savings are achieved, but control over physical infrastructure and accurate resource assessment are lost
Solution Approach 1:
The system performs preliminary assessment of network resources and applications before migration decisions are made. By analyzing traffic flow data and creating application glossaries in advance, organizations can accurately evaluate what will be migrated to the cloud, ensuring informed decisions that maintain control while achieving cost savings
Solution Approach 2:
The patent implements a feedback mechanism where traffic flow analysis continuously provides information about network resource usage and application dependencies. This feedback loop enables organizations to maintain awareness and control of their infrastructure even as they transition to cloud services, allowing for accurate resource assessment and migration planning
3Adaptability or versatility
If applications are migrated to cloud environments, then flexibility and cost efficiency improve, but the complexity of identifying and grouping applications for migration increases
Solution Approach 1:
The system segments applications into distinct groups based on their traffic flow patterns and dependencies. By analyzing network traffic data, the patent automatically divides the application portfolio into migration-ready groups, reducing the complexity of identifying which applications to migrate and how to group them for cloud deployment
Solution Approach 2:
The system enables self-service automated grouping of applications for migration. By analyzing traffic flow data and application dependencies, the system automatically creates migration groups without requiring manual intervention, thereby reducing complexity while maintaining flexibility in migration planning
Data Source
AI summary
A method of staging a move group of applications of a network is provided and includes the step of developing a reference base of applications via monitoring traffic flow between devices of the network on which applications are executed or accessing information about such applications. The method further includes the step of classifying each such selected application as a member of one of the classification sub-sets with regard to applications of the reference application base. Additionally, the method includes the step of accessing information about the classification sub-sets of those respective applications executed on each of a target group of devices to thereby form an application classification glossary associated with the device.