arXiv (All)
open access
Efficient algorithms for collecting the statistics of large-scale IP address data
Compiling the statistics of large-scale IP address data is an essential task in network traffic measurement. The statistical results are used to evaluate the potential impact of user behaviors on network traffic. This requires algorithms that are capable of storing and retrieving a high volume of IP
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- data plane systems for network monitoring and packet scheduling in programmable networks#194375
- Information Elements for Data Link Layer Traffic Measurement#399018
- A One-Way Loss Metric for IP Performance Metrics (IPPM)#399268
- AR-based MEP Progress Monitoring using BIM and Synthetic Data#7835
- What is Normal? A Big Data Observational Science Model of Anonymized Internet Traffic#665455
Record · ID 1051935
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive