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2 attachment feature that will enable various SOAP bindings to be de ned that support the exchange of messages with binary attachments In addition to SwA, another attachments speci cation, WS-Attachments [18], is also referenced by the SOAP 12 Attachment Feature WS-Attachments leverages DIME rather than MIME as the document attachment mechanism DIME has the advantage of maintaining a length attribute for each payload component Knowing the length relieves the receiving SOAP application from the possible signi cant overhead in processing and memory allocation After creating the SOAP 12 Attachment Feature, the XMLP working group further analyzed the attachments space and found the existing work lacking SwA did not fully consider attachments relative to the XML Infoset and SOAP processing model expressed in SOAP 12 Additionally, opportunities for optimizing the exchange of SOAP messages that contain binary data had not been explored in a standard body.

where yt is the normalized data, and min and max denote the minimum and maximum values of zt ; t 1; . . . ; N. The performance of the forecasting models was evaluated using the root mean square error (RMSE) (4.19) and the nondimensional error index (NDEI) (4.20). The ePL model adopted the following values: b t 0:30, r 0:25, and l 0:35. These are the only parameters of the ePL algorithm that need to be chosen by the user. The ePL found ve rules during the 30-day development period. During testing, ePL uses hourly loads data and runs as in online mode. An MLP with the same structure and initial parameters as that developed for the Box & Jenkins benchmark was used to forecast loads in the period. MLP training also started with small, randomly chosen initial weights and took 5000 epochs to converge. Load forecasting for the same time period also has been done using ANFIS. The structure and parameters are also the same those used for the Box & Jenkins problem, and the maximum number of epochs was 1000. The eTS and xTS models were developed considering the rst 30 days before the testing period. The value of the cluster radii for the eTS model was r 0.4. Both eTS and xTS models adopted P0 750 to initialize the recursive least squares. In the experiments reported here, we ran the eTS and xTS implementation given in [9]. Table 4.2 shows the performance of the models during the testing period (24 hours), considering the two error criteria (4.19) and (4.20). The table also includes the nal

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We consider the problem of cooperative reachback in the context of extremely dense large-scale networks. In fact, the approach we take to studying these networks is to assume that the number of nodes in a nite-area network grows unbounded. That is, we consider an asymptotically dense network as a close approximation for realistic large-scale dense networks. Whereas in nitely large networks consisting of nodes with zero mass are clearly not realizable by physical devices, there is a trend toward miniaturization of these devices. For example, in recent work, a hardware simulation and deployment platform for wireless sensor networks capable of simulating networks with on the

where ^k is the model output. We consider the following case: 200 training data y examples to initialize the fuzzy rule base and the remaining 90 data pairs to test and validate. Model evaluation is performed considering the root mean square error (RMSE) and the nondimensional error index (NDEI), which is the ratio between the RMSE and the standard deviation of the target data. These indexes are computed using the following expressions: !1=2 N 1X dk ^k 2 y 4:19 RMSE N k 1 NDEI RMSE std dk 4:20

To this end, the XMLP working group has created a trio of new speci cations XML-binary Optimization Packaging [25] (XOP, pronounced zop ) is an optimized serialization of an XML Infoset that contains binary content Content that is typically base64 encoded is transmitted instead in its native octet stream, thus it does not incur either the message bloat or processing overhead associated with base64 encoding binary data XOP uses MIME Multipart/Related [26] as its packaging format Also, XOP enables binary data to be conceptualized as typical base64-encoded so it can be processed as a typical XML document This layering thus enables a.

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