Complex Network Analysis and Intelligent Monitoring Platform (Final Report)
Big data has emerged as a driving force for scientific discoveries. Large scientific instruments (e.g., colliders, light sources, and telescopes) generate exponentially increasing volumes of data. Currently, Large Hadron Collider (LHC) experiments generate hundreds of petabytes of data per year. The aggregated amount of climate science data is expected to exceed 100 exabytes by 2020. To enable scientific discovery, science data must be collected, indexed, archived, shared, and analyzed, typically in a widely distributed, highly collaborative manner over an optimized network [3-8]. The efficient movement of science data over networks is critical to the success of any such endeavor. The networks themselves produce significant metadata and complex network metric data as a result of the applications running on them. These complex network Big Data possess a wealth of intelligence and insights that can be leveraged to drive advancement. Thus, Big data analytics has become a mainstream goal in the communications industry. Yet, the sharing and application/usage of analytics insight with multiple parties is in its nascent stages. Service providers are at different maturity levels of applying big data analytics.
- Research Organization:
- Data Products LLC
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- SC0018490
- OSTI ID:
- 1496582
- Type / Phase:
- SBIR (Phase I)
- Report Number(s):
- DOE-DATA-18490; 3126391539
- Country of Publication:
- United States
- Language:
- English
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