Dynamic Session Map Token for Network Packet Tracing
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Solution Overview
Problem
Network administrators face challenges in identifying and troubleshooting issues in complex computer networks due to the difficulty in creating comprehensive session maps, especially with dynamic signaling schemes, where it's hard to predict involved elements and filter relevant packets, leading to inefficient logging and diagnosis.
Innovation Solution
The creation of dynamic session maps (DSM) that generate a unique token for packets to track interactions between signaling nodes and media engines, allowing for real-time visualization of network conditions by instructing nodes to send copies of packets to specified destinations, enabling granular tracing of packet paths and network failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive packet logging is performed across all network nodes, then complete network interaction data is obtained, but system complexity and resource consumption increase significantly
Solution Approach 1:
The patent extracts only the necessary packet copies for analysis by injecting tokens that instruct specific nodes to replicate packets. Instead of logging all packets everywhere, the system selectively extracts relevant packet copies at specific nodes based on session context, reducing overall system complexity while maintaining diagnostic completeness.
Solution Approach 2:
The logging function is segmented and distributed across multiple network nodes rather than centralized. Each node independently processes tokens and handles packet replication locally, dividing the comprehensive logging task into manageable segments that reduce individual node complexity while achieving system-wide coverage.
2Productivity
If packet filtering is applied to identify relevant traffic, then logging efficiency improves, but relevant packets may be missed in dynamic signaling schemes
Solution Approach 1:
The system performs preliminary actions by injecting tokens into packets before they traverse the network. These tokens pre-identify relevant packets and instruct nodes to replicate them, ensuring that logging efficiency is improved upfront without risking the loss of relevant packets during dynamic signaling operations.
Solution Approach 2:
The token mechanism provides feedback to network nodes about which packets require replication. Nodes receive instructions from tokens to selectively copy packets based on session context, creating a feedback loop that ensures relevant packets are captured while maintaining logging efficiency through intelligent selection rather than brute-force comprehensive logging.
3Loss of information
If network sniffers are deployed to capture traffic, then packet data can be analyzed, but it is difficult to predict where sniffers are needed in dynamic networks
Solution Approach 1:
The network nodes themselves perform the packet capture function by processing tokens and replicating packets locally. Instead of requiring external sniffers to be strategically deployed, the system enables nodes to serve their own logging needs autonomously, eliminating the difficulty of predicting and deploying sniffers in dynamic network environments.
Solution Approach 2:
The token acts as an intermediary that carries instructions from the analysis system to network nodes. This intermediary mechanism enables remote control of packet replication without requiring physical sniffer deployment, allowing the system to obtain packet data from any node in the network through software-based instruction rather than hardware deployment.
4Loss of information
If all packets are logged at every node, then complete diagnostic information is available, but the solution does not scale to larger networks
Solution Approach 1:
The system extracts only the essential diagnostic information by using tokens to selectively replicate packets at specific nodes. This extraction approach provides complete diagnostic information for analysis while avoiding the scaling problems of comprehensive universal logging, as each node only processes and replicates packets when instructed by tokens.
Solution Approach 2:
Instead of performing excessive comprehensive logging at all nodes, the system applies partial action by selectively replicating packets only where and when needed based on session context. This partial replication strategy maintains diagnostic information completeness while significantly reducing the complexity and improving scalability to larger networks.
Data Source
AI summary
Systems, methods, and non-transitory computer-readable storage media for creating dynamic session maps. The method is discussed in terms of a system implementing the method. The system generates a dynamic session map token for a packet in a communication session, wherein the dynamic session map token instructs a node to send a copy of the packet to a specified destination. The dynamic session map token includes a unique dynamic session map identifier, a port number, and an IP address associated with the specified destination. Next, the system adds the dynamic session map token to the packet to yield a tracing packet. The dynamic session map token can be incorporated into the header portion of the packet, for example. Finally, the system transmits the tracing packet to the node. In one embodiment, the system also sends the copy of the packet to the specified destination.