Exploring Network-Wide Flow Data With Flowyager

Abstract

Many network operations, ranging from attack investigation and mitigation to traffic management, require answering network-wide flow queries in seconds. Although flow records are collected at each router, using available traffic capture utilities, querying the resulting datasets from hundreds of routers across sites and over time, remains a significant challenge due to the sheer traffic volume and distributed nature of flow records. In this paper, we investigate how to improve the response time for a priori unknown network-wide queries. We present Flowyager, a system that is built on top of existing traffic capture utilities. Flowyager generates and analyzes tree data structures, that we call Flowtrees, which are succinct summaries of the raw flow data available by capture utilities. Flowtrees are self-adjusted data structures that drastically reduce space and transfer requirements, by 75% to 95%, compared to raw flow records. Flowyager manages the storage and transfers of Flowtrees, supports Flowtree operators, and provides a structured query language for answering flow queries across sites and time periods. By deploying a Flowyager prototype at both a large Internet Exchange Point and a Tier-1 Internet Service Provider, we showcase its capabilities for networks with hundreds of router interfaces. Our results show that the query response time can be reduced by an order of magnitude when compared with alternative data analytics platforms. Thus, Flowyager enables interactive network-wide queries and offers unprecedented drill-down capabilities to, e.g., identify DDoS culprits, pinpoint the involved sites, and determine the length of the attack. 1 NetFlow is a Cisco trademark, so other vendors market the NetFlow support with other names, e.g., Juniper Networks use the trademark Jflow or cflowd. 2 NetFlow and IPFIX capabilities are available in router series, e.g., Cisco IOS-XR, IOS and Catalyst router [

Discovery of Flow Splitting Ratios in ISP Networks with Measurement Noise

“…Contrary to other papers that use linear objective functions, we employ quadratic optimization that is better suited for this application domain. From the network monitoring research, network traffic analysis and visualization tools like NVisionIP [25], Flowyager [26] and VITALflow [27] have been designed for the purpose of network security [25,28,29] and management [26,27]. To the best of our knowledge, none of these tools can reliably project the flow traffic on each link, unless making assumptions on the underlying router configurations, which can be difficult to obtain for larger networks.…”