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Influencing the path that traffic takes in the network can increase revenues in two ways: 1 Offering new services with extra guarantees 2 Lowering the investment in new network resources (primarily bandwidth) by improving the utilization of existing resources Offering new services means any guarantee that the operator can charge extra money for One example is the guaranteed bandwidth service , which simply means that a certain amount of bandwidth is available for a particular customer s traffic, both in the steady state and under failure conditions Improving resource utilization means avoiding a situation where part of the network is congested while other parts are underutilized For example, if some part of the traffic is routed around a congested link on to a path where enough bandwidth is available, the upgrade of the congested link can be delayed.

According to ITU-T Recommendation J.66, one high-quality audio signal can be associated with an analogue TV video signal by time division multiplexing (TDM), using the horizontal blanking time slot which is available for synchronization at the beginning of each TV line. This method, called "sound-in-sync" (SIS) is implemented in some terrestrial and satellite TV links and, in particular, in the EBU EUTELSAT system. The main characteristics of this SIS method are listed below: the audio signal is sampled at twice the TV line frequency, i.e. at about 30 kHz; the audio signal is PCM encoded with 10 bits per sample; therefore, 20 bits (plus 1 cue bit) are inserted (after buffering) in each line synchronization time interval (i.e. about 42 to 5.8 s); emphasis in compliance with ITU-T Recommendation V.17 and companding are used in order to obtain a signal-to-noise ratio (weighted) of 56 dB. Codecs for SIS encoding-decoding are commercially available. The FM TV modem must be compatible with the transmission of the SIS pulses (see 7.5.5.3).

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Avoiding congestion also means better quality for the customer traffic: less loss, less delay and better throughput Another important cost-saving measure achieved through traffic engineering is increasing the maximum percentage of link utilization Operators constantly monitor link utilization to determine at which point it is necessary to schedule a link upgrade Each network has its own upgrade rules, expressed in terms of the percentage of link utilization that triggers an upgrade A typical rule is to upgrade at 50% utilization, to be able to accommodate traffic shifting from a failed link The benefit of traffic engineering in this context is that it can allow a higher utilization of the links, because there is more control over the path that traffic takes in the network, both under normal operation and in the failure case By increasing the average percentage of link utilization, the upgrade of links can be delayed.

Mod95: ArtS9.11A(Res46)

The supported wildcard characters are as follows:

From this discussion, it should be clear that traffic engineering is not always required If bandwidth resources are plentiful or utilization is low, there will be no congestion, not even following a link failure If there are no high-latency links in the network, there is no need to worry about traffic crossing high-latency links Indeed, as seen in the Foundations chapter of this book ( 1), not all MPLS deployments are used for traffic engineering, and depending on the label distribution protocol used, not all MPLS.

There are lots of ways to set up a DHCP server. I recommend that you refer to the dhcpd.conf man page (type man dhcpd.conf), as well as other man pages (dhcrelay, dhcpd, dhcpd.leases, and dhcp-eval) for further information on configuring DHCP.

Tangent space, 28, 29, 253 Target-oriented tracking, 6, 7, 11 Temporal motion history image (tMHI), 140 142 Texture edges, 113 matching, 5, 92, 97, 109, 113, 147, 151 memory, 58 model (or template), 3, 6, 10, 12, 34, 36, 58, 62, 78, 80, 126, 133, 147, 148, 151, 158, 213, 226 Track initiation, 7 loss detection, 165, 240 maintainance, 7, 8 Tracking pipeline, 8, 12, 13, 55, 162, 166, 214, 216, 229, 230, 232, 240 Training active shape/appearance model, 37 39, 151 AdaBoost classi er, 202, 204 autoregressive dynamics, 51, 52 background model, 94, 95 Triangulation, 61, 199 202, 204 Tukey M-estimator, 169 Twist vector, 29 Two-phase segmentation, 109, 111 Unscented information lter, 178 Kalman lter, 51, 164, 166, 174, 176, 178, 216 transform, 164, 176, 180 Update online features, 9, 94, 95, 104, 112, 120, 122, 127, 133, 142, 148, 151 pose (see also Pose), 28, 29, 30, 41, 50, 51, 168, 245, 253 state estimate, 2, 6, 9, 44, 175, 176

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eaders of many of the open source projects covered in this book graciously agreed to provide technical reviews of the chapters that covered their work There s nothing like having someone who eats, sleeps, and breathes a project suggesting corrections and enhancements to your writing.

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