Load shedding in stream databases: a control-based approach
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Load shedding in network monitoring applications
ATC'07 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference
GS-TMS: a global stream-based threat monitor system
Proceedings of the VLDB Endowment
Robust network monitoring in the presence of non-cooperative traffic queries
Computer Networks: The International Journal of Computer and Telecommunications Networking
Counting Flows over Sliding Windows in High Speed Networks
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Declarative composition routing protocols adaptation in MANET using rough set theory
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
On-line predictive load shedding for network monitoring
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
Self-organization of wireless networks through declarative local communication
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems - Volume Part I
Predictive resource management of multiple monitoring applications
IEEE/ACM Transactions on Networking (TON)
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Many of the data sources used in stream query processing are known to exhibit bursty behavior. We focus here on passive network monitoring, an application in which the data rates typically exhibit a large peak-to-average ratio. Provisioning a stream query processor to handle peak rates in such a setting can be prohibitively expensive. In this paper, we propose to solve this problem by provisioning the query processor for typical data rates instead of much higher peak data rates. To enable this strategy, we present mechanisms and policies for managing the tradeoffs between the latency and accuracy of query results when bursts exceed the steady-state capacity of the query processor. We describe the current status of our implementation and present experimental results on a testbed network monitoring application to demonstrate the utility of our approach