One of TCP's critical tasks is to determine which packets are lost in the network, as a basis for control actions (flow control and packet retransmission). Modern TCP implementations use two mechanisms: timeout, and fast retransmit. Detection via timeout is necessarily a time-consuming operation; fast retransmit, while much quicker, is only effective for a small fraction of packet losses. In this paper we consider the problem of packet loss detection in TCP more generally. We concentrate on the fact that TCP's control actions are necessarily triggered by inference of packet loss, rather than conclusive knowledge. This suggests that one might analyze TCP's packet loss detection in a standard inferencing framework based on probability of detection and probability of false alarm. This paper makes two contributions to that end: first, we study an example of more general packet loss inference, namely optimal Bayesian packet loss detection based on round trip time. We show that for long-lived flows, it is frequently possible to achieve high detection probability and low false alarm probability based on measured round trip time. Second, we construct an analytic performance model that incorporates general packet loss inference into TCP. We show that for realistic detection and false alarm probabilities (as are achievable via our Bayesian detector) and for moderate packet loss rates, the use of more general packet loss inference in TCP can improve throughput by as much as 25%.

The huge number and the textual nature of Web documents have created the need for search engines. In this kind of system the user's queries are answered based on a static view of the whole or part of the Web. However, the Web is a dynamic system and its documents are inserted, changed and removed frequently, thus creating an inconsistency between the state of the Web and the static view of the documents of the search engine. We describe the dynamic aspects of the HTML documents of the Brazilian Web, namely the rate of insertion, change and removal of its documents, from the point of view of search engines. We also describe the tools we used to support this study. Whenever possible, we compare measures of the Brazilian Web with related measures of the World Wide Web. We show how the study of these aspects can be used in search engines to improve the quality of its services, in particular, aspects related to robots or spiders.