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Summary Table 22 summarizes the properties of the static networks analyzed so far, including acyclic and cyclic meshes with up to three dimensions Many other static network topologies have been proposed in the past: most notably, topologies that are constructed modularly by substituting the nodes of one topology with subtopologies A detailed study of more sophisticated topologies and further reading can be found in Cosnard and Trystram [45], Culler and Singh [48], Grama et al [82], and Quinn [156] 222 Dynamic Networks In contrast to static networks, dynamic networks establish the connection between the units of the parallel system on demand The connections are made through internal network switches that are not associated with any processor hence the alternative name of indirect network This is in contrast to static networks, where every switch is implicitly associated with one processor; see Figure 25 A dynamic network is constituted by a set of switches, which route the communication through the network from its source to its destination Crossbars The most powerful dynamic network is a crossbar It employs a grid of nm switches to connect n units on one side with m units on the other side, as illustrated in Figure 29 Through this simple approach, it is a nonblocking network; that is, a connection between unit i on the left and unit j at the top does not block the connection of any other unit on the left with any other unit at the topAn example of this nonblocking behavior is shown in Figure 29(b) From the static networks considered in Section 221, only the fully connected network has the same nonblocking property However, it also comes at a similar cost, as the number of switches in a crossbar has the same complexity as the number of links in a fully connected network, namely, O( p2 ).



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[4] and Assun ao and Ghanbari [5] who adopted UDP as the network transport; and c the studies by Cuetos and Ross [1], Cuetos et al [2], and Jacobs and Eleftheriadis [3] which adopted TCP as the network transport A common property of these adaptation algorithms is the existence of a con gurable operating parameter [1 2], which is typically used in the feedback loop of the algorithms Not surprisingly, as will be illustrated in Section 86, the choice of this operation parameter can signi cantly affect the performance of the rate adaptation algorithm Unfortunately, to optimize this parameter for the best performance will require a priori knowledge of the available network bandwidth over the entire duration of the video session This is clearly not possible in practice and thus poses signi cant dif culties to deploying these rate adaptation algorithms.

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In this chapter, we address this issue by presenting a rate adaptation algorithm that does not have any con gurable parameter In other words, prior knowledge of the available network bandwidth is not needed to run the rate adaptation algorithm Our results show that compared to the existing algorithms, the presented algorithm can achieve comparable or even better performance and does so without the need to tweak any operating parameters..

Figure 29 An 8 8 crossbar; (a) the source and destination units are connected to the numbered lines; (b) nonblocking communication routing in the crossbar The squares represent the switches

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13 May 2015 ... Solution. Start IJ Scan Utility. Starting IJ Scan Utility. Click Settings.... The Settings dialog appears. Click Document Scan. Select Start OCR for Application Settings, then select the application in which you want to display the result. Note. Click OK. The IJ Scan Utility main screen appears. Click Document.

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In this section, we review some related work on adapting video to cope with the bandwidth uctuations in the Internet. Assun ao and Ghanbari [5] and Kanakia et al. [6] proposed adapting c the data pumping rate and hence the bit-rate of video by adjusting the quantizer scales of the frames. The data pumping rate is controlled dynamically based on the buffer occupancy of the bottleneck switch. The idea is to maintain the buffer occupancy of the bottleneck switch at a safe level to avoid losses of video packets due to buffer over ow. Their approach can effectively adapt to network congestion and reduce packet losses. The only limitation is that we need to know the buffer occupancy at the bottleneck router. This may require modi cation to the router rmware to support this function. Rejaie et al. [4] proposed an adaptive streaming scheme running on its proprietary RAP congestion control protocol [11] with the support of multi-layer-encoded videos. They proposed the criteria for adding or dropping a layer of video based on the current sending rate of its rate-based RAP congestion control protocol. This approach requires the commercial streaming player software to support playback of layered-encoded video. Jacobs and Eleftheriadis [3] proposed a video adaptation scheme that controls the video bit-rate using transcoding. The proposed system runs on a custom-designed semi-reliable congestion control protocol. The main idea of the adaptation algorithm is to maintain the server buffer occupancy at a certain level. The algorithm assumes that video data are input

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