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The proposed neural network controller (NNC) is for user/server level dynamic buffer tuning. It eliminates overflow by making the buffer length always cover the queue length adaptively on the fly. The NNC and the AQM (active queue management) mechanism(s) at the system/router level together form a unified buffer overflow prevention solution for the TCP channels. The NNC provides the following advantages: a) it prevents the AQM resources dished out already at the system level from being wasted, b) it shortens the service roundtrip time (RTT) by eliminating the chance of retransmission due to user-level overflow, and c) it alleviates network congestion. The NNC operates by the {0,/spl Delta/}/sup 2/ objective function and the principle is to maintain the given /spl Delta/ safety margin about the reference point symbolically represented by the "0" in {0,/spl Delta/}/sup 2/. The NNC stability and precision are traffic pattern independent for its statistical nature. This independence makes the NNC immensely suitable for Internet applications because Internet traffic can be LRD (long-range dependence), SRD (short-range dependence) or multifractal, and switch suddenly.

The novel RTPD/MACSC model proposed in this paper tunes the cache size adoptively on the fly. It combines the extant MACSC (model for adaptive cache size control) and the novel RTPD (real-time traffic pattern detection) capability. Similar to its MACSC predecessor, the new RTPD/MACSC tuner maintains the given cache hit ratio consistently and persistently. It, however, differs from its predecessor because it adapts itself to compensate for the ill effects on the cache hit ratio by the Internet traffic, which embeds various patterns over time. The automatic adaptation (self-tuning) capability in response to traffic pattern changes detected by the RTPD is called self-reconfiguration in the RTPD/MACSC context.