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 highthroughput, 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

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... 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) categoryspecific management of shared state, and (2) adaptive flowlevel 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.