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When a CAMEL service is invoked at PDP context establishment acknowledgement, it may apply the following control to this PDP context: allow the acknowledgement of the PDP context; the PDP context may now be used for data transfer release the PDP context It is not possible for the CAMEL service invoked at PDP context establishment acknowledgement to modify the APN PDP Context Establishment The present section describes the process of PDP context establishment by a subscriber and how a CAMEL service may control the PDP context When the subscriber establishes a PDP context, the UE sends the Activate PDP context request DTAP message to the SGSN This DTAP message may contain parameters such as APN, requested QoS and requested PDP address If GPRS-CSI is present in the SGSN for this subscriber and the GPRS-CSI contains TDP PDP context establishment, then the PDP context establishment results in the invocation of a CAMEL service from the SGSN There are no trigger conditions associated with GPRS-CSI, such as a list of APNs That means that every time the subscriber establishes a PDP context, a CAMEL service will be invoked If the CAMEL services decides that for this PDP context no CAMEL control is required, then the service may send CAP CUE-GPRS; PDP context establishment now continues without CAMEL control The details of the CAMEL service to be invoked are retrieved from GPRS-CSI Speci cally, the gsmSCF address and service key are used to invoke the CAMEL service It is permissible for a subscriber to establish a PDP context without supplying an APN In that case, the SGSN would select a default APN for this PDP context27 At this point in the PDP context establishment process, no APN analysis has taken place yet in the SGSN This implies that the APN as received from the UE is reported to the CAMEL service If the subscriber did not provide an APN, then the CAMEL service is invoked without reporting an APN to the SCP The CAMEL service has now gained control over the PDP context The control.

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Together (244) and (245) lead to this remarkable result: the long-run fraction of customers nding the system out of stock = the long-run fraction of time the system is out of stock (246)

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The relations (243) and (246) are particular instances of the property Poisson arrivals see time averages Roughly stated, this property expresses that in statistical equilibrium the distribution of the state of the system just prior to an arrival epoch is the same as the distribution of the state of the system at an arbitrary epoch when arrivals occur according to a Poisson process An intuitive explanation of the property Poisson arrivals see time averages is that Poisson arrivals occur completely randomly in time; cf Theorem 115 Next we discuss the property of Poisson arrivals see time averages in a broader context For ease of presentation we use the terminology of Poisson arrivals However, the results below also apply to Poisson processes in other contexts For some

speci c problem let the continuous-time stochastic process {X(t), t 0} describe the evolution of the state of a system and let {N (t), t 0} be a renewal process describing arrivals to that system As examples: (a) X(t) is the number of customers present at time t in a queueing system (b) X(t) describes jointly the inventory level and the prevailing production rate at time t in a production/inventory problem with a variable production rate It is assumed that the arrival process {N (t), t 0} can be seen as an exogenous factor to the system and is not affected by the system itself More precisely, the following assumption is made Lack of anticipation assumption For each u 0 the future arrivals occurring after time u are independent of the history of the process {X(t)} up to time u It is not necessary to specify how the arrival process {N (t)} precisely interacts with the state process {X(t)} Denoting by n the nth arrival epoch, let the random variable Xn be de ned by X( n ) In other words, Xn = the state of the system just prior to the nth arrival epoch Let B be any set of states for the {X(t)} process For each t 0, de ne the indicator variable IB (t) = 1 0 if X(t) B, otherwise

Also, for each n = 1, 2, , de ne the indicator variable In (B) by In (B) = 1 0 if Xn B, otherwise

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The technical assumption is made that the sample paths of the continuous-time process {IB (t), t 0} are right-continuous and have left-hand limits In practical situations this assumption is always satis ed Theorem 241 (Poisson arrivals see time averages) Suppose that the arrival process {N (t)} is a Poisson process with rate Then: (a) For any t > 0, E[number of arrivals in (0, t) nding the system in the set B] = E

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