CiteSeerX — Table search results — On the use of random neural networks for traffic matrix estimation in large-scale IP networks

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Table 1: Large-scale network models

in BIOLOGICALLY INSPIRED DISCRETE EVENT NETWORK MODELING * Technical Education Faculty

by unknown authors

"... In PAGE 7: ... Figure 6: Throughput comparison of different algorithms Figure 7: Average packet delay comparison Performance of the framework on increased scalability and connectivity In our experiments, one of the key independent variables was the degree of connectivity and scalability. In order to examine the scalability aspect of our approach, we developed various networks ranging from 29 to 3520 components (see Table1 ). These models were executed with acceptable performance in the DEVSJAVA environment.... ..."

Table 7. Comparison of imputation procedures for three large-scale databases

in Large-Scale Imputation For Complex Surveys

by David A. Marker, David R. Judkins, Marianne Winglee 2002

"... In PAGE 37: ... Procedures are in development for properly estimating the accuracy of such estimates. Table7 compares the hot-deck imputation procedures used in the three large-scale databases described in this chapter. Table 7.... ..."

Cited by 1

Table 2. Comparison of pass rates of multipath fading distributions using full band

in SUB-BAND ANALYSIS IN UWB RADIO CHANNEL MODELING

by Lassi Hentilä, Veikko Hovinen, Matti Hämäläinen

"... In PAGE 3: ... Tables below show, how different CDFs fit to the data. Table2 depicts all of the measurement environments from LOS to NLOS2 (c.f.... ..."

Table 2 Large-scale scenarios

in IPv6 deployment: Real time applications and QoS aspects

by C. Bouras, A. Gkamas, D. Primpas, K. Stamos 2005

"... In PAGE 5: ...3. Large-scale scenarios The setup for each scenario is displayed in Table2 . They have been designed so that we could investigate the effectiveness and characteristics of the implemented QoS mechanisms in order to provide a measurable improvement to various types of traffic that has been marked as premium traffic.... ..."

Table 2 Large-scale scenarios

in IPv6 deployment: Real time applications and QoS aspects

by C. Bouras, A. Gkamas, D. Primpas, K. Stamos 2005

Table 2 Large-scale scenarios

in Abstract IPv6 deployment: Real time applications and QoS aspects *

by C. Bouras A, A. Gkamas A, D. Primpas A, K. Stamos A 2005

Table 4: Comparison of computational times of a large-scale system benchmark

in unknown title

by unknown authors 2005

"... In PAGE 15: ...1 seconds. In Table4 , we show the computational times when varying both Rf and Rs from one to 10 000 reactions. The largest benchmark reaction network then has 20 000 reactions and 50 000 chemical species.... ..."

Table 1. Wireless Medium Model Large-scale path loss

in Building Robust Wireless LAN for Industrial Control with DSSS-CDMA Cellphone Network Paradigm

by Qixin Wang, Weiqun Chen, Wenbo He, Marco Caccamo 2005

"... In PAGE 8: ... The external RF interference source is turned on at time 5sec and turned off at time 15sec. The wireless medium instance is generated according to the random model de- scribed in Table1 . The model is typical for indoor indus- trial environments [31][34].... ..."

Cited by 3

Table 1. Wireless Medium Model Large-scale path loss

in Building Robust Wireless LAN for Industrial Control with DSSS-CDMA Cellphone Network Paradigm

by Qixin Wang, Xue Liu, Weiqun Chen, Wenbo He, Marco Caccamo 2005

Cited by 3

Table 5-3 An extract of the sample of the large-scale experiment.

in Ontology-Driven Geographic Information Systems

by Frederico Torres Fonseca, Frederico Torres Fonseca, Dr. Max, J. Egenhofer

"... In PAGE 10: ...List of Tables Table5 -1 Extract from the results of the small-scale experiment .... In PAGE 10: ...able 5-1 Extract from the results of the small-scale experiment .................................... 80 Table5 -2 A summary of the results of the small-scale experiment.... In PAGE 10: ...able 5-2 A summary of the results of the small-scale experiment.................................. 81 Table5... In PAGE 92: ... The potential for information integration was recorded for four types of measurement: (1) using hierarchies and roles, (2) using roles alone, (3) using hierarchies alone, and (4) using neither hierarchies nor roles. A sample of the results is shown in Table5 -1. The results for the potential of information that could be matched for (1) and (2) are the same because the method for evaluation for both gives a maximum of 1 for the match of an entity with an entity or the match of an entity with a parent of an entity.... In PAGE 93: ...33 382 706 0.54 Table5 -1 Extract from the results of the small-scale experiment For instance, for the measurement of the potential for information integration using roles alone we had a mean of 184.89 and a standard deviation of 24.... In PAGE 93: ...037. Table5 -2 shows the mean and standard deviation of the non- normalized and normalized measurements of the potential for information integration using no roles and no hierarchies, using hierarchies alone, using roles alone, and using... In PAGE 94: ...034 0.030 Table5 -2 A summary of the results of the small-scale experiment. The results of the potential for information integration are shown in Figure 5-12.... ..."

Results 1 - 10 of 220,926

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Table 1: Large-scale network models

Table 7. Comparison of imputation procedures for three large-scale databases

Table 2. Comparison of pass rates of multipath fading distributions using full band

Table 2 Large-scale scenarios

Table 2 Large-scale scenarios

Table 2 Large-scale scenarios

Table 4: Comparison of computational times of a large-scale system benchmark

Table 1. Wireless Medium Model Large-scale path loss

Table 1. Wireless Medium Model Large-scale path loss

Table 5-3 An extract of the sample of the large-scale experiment.