Explaining World Wide Web Traffic Self-Similarity

Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to self-similar network traffic. We present an explanation for traffic self-similarity by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we show evidence that WWW traffic is self-similar. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites.

On the Interaction between TCP and the Wireless Channel in CDMA2000 Networks

In this work, we conducted extensive active measurements on a large nationwide CDMA2000 1xRTT network in order to characterize the impact of both the Radio Link Protocol and more importantly, the wireless scheduler, on TCP. Our measurements include standard TCP/UDP logs, as well as detailed RF layer statistics that allow observability into RF dynamics. With the help of a robust correlation measure, normalized mutual information, we were able to quantify the impact of these two RF factors on TCP performance metrics such as the round trip time, packet loss rate, instantaneous throughput etc. We show that the variable channel rate has the larger impact on TCP behavior when compared to the Radio Link Protocol. Furthermore, we expose and rank the factors that influence the assigned channel rate itself and in particular, demonstrate the sensitivity of the wireless scheduler to the data sending rate. Thus, TCP is adapting its rate to match the available network capacity, while the rate allocated by the wireless scheduler is influenced by the sender's behavior. Such a system is best described as a closed loop system with two feedback controllers, the TCP controller and the wireless scheduler, each one affecting the other's decisions. In this work, we take the first steps in characterizing such a system in a realistic environment.

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).