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Recommender Such matching is performed using the Mobile Context Ontologies and Service Ontologies to classify the services rst and to retrieve them later This process is described in more detail in the following subsection Only services that are available are matched during the discovery process; when a service is no longer available, its advertisement is removed from the SBD and it will not be found by the ME 4433 Control Flow within the BMSD Upon receiving a request of service from the Dispatcher, the service discovery process starts The Dispatcher calls the MSB Client and provides user identi er information The client uses this information to create an XML compliant le and then registers a subscription of the user with the MSB At this point the MSB generates a new thread dedicated to the subscribing user and returns a subscription identi er to the Dispatcher.

5. For configurations that use a display attached through an audio/video switchbox, or setups in which display properties are not detected automatically, you may add this option:

on the particular index that was sent. For a typical codeword, there are two different sources of error when we use jointly typical decoding: Either the output Y n is not jointly typical with the transmitted codeword or there is some other codeword that is jointly typical with Y n . The probability that the transmitted codeword and the received sequence are jointly typical goes to 1, as shown by the joint AEP. For any rival codeword, the probability that it is jointly typical with the received sequence is approximately 2 nI , and hence we can use about 2nI codewords and still have a low probability of error. We will later extend the argument to nd a code with a low maximal probability of error. Detailed calculation of the probability of error: We let W be drawn according to a uniform distribution over {1, 2, . . . , 2nR } and use jointly typical decoding W (y n ) as described in step 6. Let E = {W (Y n ) = W } denote the error event. We will calculate the average probability of error, averaged over all codewords in the codebook, and averaged over all codebooks; that is, we calculate Pr(E) =

The thread starts a cycle that periodically (eg each minute) interrogates the Recommender for services that may be useful to the user This query results in a list of categories of services that are likely to be useful to the user Upon receiving the recommendation, if the list of categories is changed with respect to the one advertised in the previous cycle, the MSB transmits the list to the Matching Engine, which selects new services to propose to the user If the user s context has not changed and the output of the Recommender remains the same, the cycle is restarted, avoiding the forwarding of redundant service lists The Matching Engine monitors the list of available services in the SDB and it loads all the context and service ontologies that describe them The context and service ontologies are used as background knowledge of the Matching Engine.

Speci cally, they are loaded in a Description Logics classi er,2 which rst derives the relations between the concepts speci ed in the ontology Such inference, technically named TBox classi cation, results in the nal taxonomy tree of all concepts Once the concept inferences are completed, the descriptions of the services in the system are classi ed using the concepts in the ontology During such classi cation, each service description is added as an instance of the service type to which it belongs For example, a service that reports weather information may be classi ed as an Environment Context Provider The process of identifying the type of services in the system is technically referenced as ABox classi cation As a consequence of this process, the Matching Engine stores an up-to-date indexing of the available services, which reduces the service matching to little more than a table lookup.