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Sophisticated middlebox services-such as network monitoring and intrusion detection, DDoS mitigation, worm scanning, XML parsing and protocol transformation-are becoming increasingly popular in today's Internet. To support high- throughput, these services are often deployed on distributed memory, multi-processor (DM-MP) hardware platforms such as a cluster of network processors. Scaling the throughput of such platforms, however, is challenging because of the difficulties and overheads of accessing persistent, shared state maintained by the services. In this paper, we describe the design and implementation of Oboe, a run-time system for DM-MP platforms that addresses the above challenge through two foundations: (1) category-specific management of shared state, and (2) adaptive flow- level load distribution for addressing persistent processor overload. Our simulations demonstrate that Oboe can achieve performance within 0-5% of an ideal adaptive system. Our prototype implementation of Oboe on a cluster of IXP2400 network processors, demonstrates the scalability achieved with increasing number of processors, number of flows and state size.
Date of Conference: 13-18 April 2008