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(There is a similar commented-out server-info section.) These relate to support for the server monitoring facilities that might be needed by a webmaster. When enabled, these are accessed using URLs, e.g. http://localhost:8080/server-status. In this case, the URL does not define a path to a file resource; it is interpreted differently. These Location directives specify how such URL requests should be handled. You should uncomment these directives, and edit the Allow subdirective to reference a domain from where you wish to read the server data. The final section of the configuration file contains options for Apaches that are acting as proxy servers, and options supporting virtual hosts . If you are able to set up a DNS server, then it is worth playing with the virtual host controls. Virtual hosts allow your Apache to pretend to be several different machines provided all the machine names are properly registered with the Domain Name Services. This is particularly useful for small Internet Service Providers who host sites for a few customers. Instead of URLs like and ~sportshop, the clients can have URLs like and http:// These all map to the same server, but (provided clients are using HTTP/1.1) the server can differentiate between the requests and really make it appear that there are multiple separate servers supporting the different clients. These features are documented at
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The Index Service [46] uses an extensible framework for managing static and dynamic data for GT3-based Grid systems. It provides the following functions: Dynamic service data creation and management via Service Data Provider components. Aggregation of service data from multiple instances. Registration of Grid service instances. Figure 2.21 shows the structure of the GT3 Index Service. The Index Service combines Service Data Provider, Service Data Aggregation, and Registry components. Service Data Provider components
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and continues the same procedure with the second strongest signal, etc., until all the users signals are detected. The main disadvantage of the SIC approach is the delay associated with demodulating the signals sequentially. In contrast to the SIC method, a parallel interference cancellation (PIC) scheme detects all the signals in parallel and subtracts the interference estimate for each user (sum of all the signal estimates except the desired user s) from the received signal. This procedure can be repeated a number of times in order to obtain better performance, by using the results of the previous step to regenerate the interference. Apart from the SIC and PIC approaches, we can consider the multistage detection principle, which is in fact a symmetrized version of the SIC technique [19]. Finally, the decision feedback approach combines several important characteristics of the SIC and multistage receivers. It basically uses the nal decisions as the feedback, and uses both the linear and nonlinear techniques for MAI mitigation [19]. For all the previous receiver structures we have considered, the receiver is assumed to know the channel. In practice, one way to obtain this information is to perform channel estimation, before the multiuser detection stage, by employing training symbols (data-aided channel estimation) [38]. Alternatively, channel estimation and data detection can be performed jointly without requiring any training data, which is called a blind (non-data aided) algorithm. In view of the similarity between the IR-UWB and CDMA systems, application of blind MUD algorithms to IR-UWB systems is possible, as considered in [40 42]. Finally, subspace approaches can be useful for UWB systems to provide lowcomplexity designs, when the rank of the covariance matrix of the discrete received signal is large. For example, the implementation of the optimal MMSE receiver in Section 10.3.2 can require the inversion of a very large matrix when many samples are to be combined optimally. Therefore, the subspace schemes determine a lowrank subspace spanned by the columns of the covariance matrix, where the design of a simpler MMSE scheme becomes possible. One way to implement this rankreduction is principal component analysis [43, 44], where the eigen-decomposition of the covariance matrix is employed to determine a signal subspace spanned by the eigenvectors associated with the largest eigenvalues and a noise subspace spanned by the eigenvectors associated with the remaining eigenvalues. Then, the received signal is projected onto this signal subspace. The application of this subspace approach to IR-UWB systems is investigated in [45]. Another technique for rankreduction is the multistage Wiener lter (MSWF) approach [46], which does not need any eigen-decomposition, and usually outperforms other rank-reduction approaches [47]. This reduced-rank approach based on the MSWF can be adopted for IR-UWB systems without any signi cant modi cation [48].
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We may, however, use compromise solutions and assist the distributed WAVE-WP interpreter in making hardware distribution decisions (especially if the hardware resources are limited) by providing a more detailed description of the problem, say, as a limited set of competing or cooperating branches but still well above the implementation layer. Each branch will move between the noncleaned polygons and clean them, while blocking other branches from visiting the occupied polygons. Visiting Polygons Only Once. With visiting polygons only once, and moving to neighboring polygons only, while checking the states of surrounding neighbors sequentially, the program, consisting of three competing branches starting in polygons 1, 4, and 7, will be as follows:
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Figure 6-13
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The objective function for network capacity fobj x can be defined as fobj x =
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