Abstract
Current methods of data classification are time-intensive due to the heavy reliance on external third-party scanners. By implementing a thin agent that intelligently optimizes CPU and memory utilization, distributes workload efficiently, and tunes high-concurrency threads based on task characteristics (e.g., data classification intelligent packet distribution), with built-in fault tolerance and incremental scanning, we achieved a dramatic 100x performance improvement.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Cohesity Inc., "Adaptive Load Balancing for Optimized Resource Utilization in Concurrent Data Processing", Technical Disclosure Commons, (March 24, 2025)
https://www.tdcommons.org/dpubs_series/7931
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