Telcordia Technologies, Inc.

Tti Inventions C LLC

Samaradasa Weerahandi

Ricardo Martija

Walter D Sincoskie

Christian F Huitema

Fu-Tak Dao

Thomas Spacek

Elisa M Santos

With respect to a current quarter of unreported revenue for certain Internet companies, by processes performed by a computer revenue to date is analytically determined and future revenue for the remaining quarter is statistically projected by modeling revenue based on 'Internet metrics'. Actual revenue performance is obtained and one or more 'Internet metrics' are measured for a given Internet company. Using the revenue and measured Internet metric data from prior quarters, a regression analysis is performed in order to generate multiple models that reflect the relationship between the Internet metrics and revenue. From these models, one is selected that will most likely yield the best revenue estimates. This resultant model and current Internet metric data are subsequently used to estimate the company's revenue for the current day, week, month, or quarter. These estimates are also used to project the company's revenue for future days, weeks, months, and quarters.

Analytically determining revenue of internet companies using internet metrics

Methods and systems are provided for determining inter-region and intra-region traffic in one or more networks. To determine the network traffic flowing between a first region and a second region, one or more routers in the first and second regions are identified along with their respective links connecting the routers in the first region to those in second region. A processor located remotely from the routers in the first and second regions then determines discrete used bandwidth samples of the identified links over a period of time. Based on the used bandwidth samples, the processor determines the network traffic flowing between the first and second regions. To determine the network traffic within a region, a sample of hosts each including one or more web servers in the region are selected. The processor identifies the last pairs of identifiable routers on respective routes from the processor to the sample hosts and the respective links connecting the identified last pairs of routers. The processor then determines discrete used bandwidth samples of the identified respective links. Based on the used bandwidth samples, the processor determines the network traffic within the region.

Method and system for remote measurement of network traffic

Methods and systems are provided for determining the geographical regions of hosts in a network. A plurality of sample hosts in the network are preselected. The sample hosts are preselected such that they are located in a plurality of geographical regions that are determinable using existing methods and systems or other means. A plurality of monitoring stations are provided in the network to determine first sets of information associated with each of the sample hosts and second sets of information associated with a host whose geographical region is to be determined. The geographical region of the host is then determined to be the same as the geographical region of those sample hosts whose respective mean of first sets of information has the shortest weighted vector (or euclidian) distance from the second sets of information.

Method and system for determining geographical regions of hosts in a network

Methods and systems are provided for identifying congestion and anomalies at individual nodes, links, and segments in a network. In accordance with an embodiment of the invention, a monitoring station determines for each link in the network a statistical model based on a harmonic analysis. The monitoring station collects from each link metric data. The monitoring station then selects for each link a model that includes one or more harmonic components. By estimating parameters of the harmonic components, the monitoring station then captures the periodicity of the collected metric data in the harmonic components of the model. The monitoring station uses the model to estimate the state of the network from which estimated values of the metric data are determined. The monitoring station then determines whether congestion or anomalies exist in the links based on the estimated metrics.

Method and system for identifying congestion and anomalies in a network

A method is provided for estimating the size of a computer network such as the Internet. A computer generates a random sample of potential network addresses and then determines whether those sample addresses are currently allocated to computers on the network. Using samples taken at multiple points in time, the computer statistically models the growth of the network. The model has unknown parameters, and values of the parameters are estimated using previously sampled data. Using the estimated parameter values in the model, the computer estimates the number of computers on the network at historical points in time. The computer also uses the model to forecast the number of computers on the network at future points in time.

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Pittstown, NJ, United States of America

Samaradasa Weerahandi