A Survey on Big Data for Network Traffic Monitoring and Analysis
| Autor: | Idilio Drago, Pedro Casas, Alessandro D'Alconzo, Marco Mellia, Andrea Morichetta |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Big Data Computer Networks and Communications Computer science Big data 02 engineering and technology Big Data Network Monitoring Data modeling Computer Science - Networking and Internet Architecture Network Monitoring 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Networking and Internet Architecture (cs.NI) business.industry 020206 networking & telecommunications Network monitoring Data science Network management Traffic classification Computer Science - Distributed Parallel and Cluster Computing Scalability Anomaly detection The Internet Distributed Parallel and Cluster Computing (cs.DC) business |
| Popis: | Network Traffic Monitoring and Analysis (NTMA) represents a key component for network management, especially to guarantee the correct operation of large-scale networks such as the Internet. As the complexity of Internet services and the volume of traffic continue to increase, it becomes difficult to design scalable NTMA applications. Applications such as traffic classification and policing require real-time and scalable approaches. Anomaly detection and security mechanisms require to quickly identify and react to unpredictable events while processing millions of heterogeneous events. At last, the system has to collect, store, and process massive sets of historical data for post-mortem analysis. Those are precisely the challenges faced by general big data approaches: Volume, Velocity, Variety, and Veracity. This survey brings together NTMA and big data. We catalog previous work on NTMA that adopt big data approaches to understand to what extent the potential of big data is being explored in NTMA. This survey mainly focuses on approaches and technologies to manage the big NTMA data, additionally briefly discussing big data analytics (e.g., machine learning) for the sake of NTMA. Finally, we provide guidelines for future work, discussing lessons learned, and research directions. |
| Databáze: | OpenAIRE |
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