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subnet-speci c admission control architecture can be implemented using, for example, the Subnet Bandwidth Manager (SBM) scheme [RFC2815], an implementation of the Integrated Services (IntServ) architecture [RFC1633] of IETF for LANs IEEE has de ned a standard for mobility between access points, but support for mobility between access routers requires another protocol, such as Mobile IP In the same vein, end-to-end service quality support architecture would need other building blocks apart from 8021 technologies and SBM The IETF has many standards that could serve as building blocks; analogously to the 3GPP R5 SIP inter-working described above, an IETF speci cation exists for correlating SIP sessions to available service quality support in the network [RFC3312] The basic problem is that there is no standard end-to-end service quality support architecture for WLAN in IETF.



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For now, we note that these independence assumptions will greatly reduce the number of probabilities required to specify the probability distribution among the variables in the network11 To specify the probability distribution of a Bayesian network, one must provide two types of probabilities: (1) the prior probabilities of the root nodes (nodes with no parents) and (2) the conditional probabilities of all nonroot nodes given all combinations of its parent nodes Let us look at a speci c example See Figure 813, which is the same Bayesian network described earlier There are two root nodes, mechanical failure and bad weather, and their prior probabilities are indicated in Figure 813 By prior probability we mean the probability of an event occurring before any evidence is introduced The prior probability of mechanical failure occurring is given by P(M1) = 0.

m f = kt - f i t - 1





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1, whereas the prior probability of bad weather is P(B1) = 02 In addition, Figure 813 includes the conditional probabilities of all nonroot nodes, given all possible combinations of their parent nodes For example, for the node plane late, we must consider all combinations of mechanical failure and bad weather, its two parent nodes Hence the conditional probabilities P(P1| M1, B1), P(P1| M1, B2), P(P1| M2, B1), and P(P1| M2,B2) all need to be speci ed We do not need to specify the conditional probabilities for the event M2, because it is assumed that P(M2) = 1 P(M1) by Eq 83 Where do these prior and conditional probabilities come from If we are fortunate enough, they are based on historical data For example, we may have records that indicate that 10% of the time a plane will experience a mechanical failure.

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Summarizing the above information, the 3GPP architecture has both advanced architectural service quality support means, and a service quality support model at the correct level of abstraction For other technologies such as 80211 and other LAN technologies, there is currently no comparable architectural support for service quality This means that end-user experience for advanced services such as multimedia streaming and multimedia conferencing cannot be engineered with the same degree of accuracy as for UMTS Typically, the service quality would depend on the number of concurrent users of the same service Thus, a service model targeting multi-access environment in future systems needs to be able to account for not only differences in bandwidth, but also in service quality support capabilities Ongoing standardization efforts in 3GPP Release 6 target integration of WLAN access into 3GPP core network as one access technology [AHP03].

CONTROL TYPE FLAGS ICC_BAR_CLASSES ICC_COOL_CLASSES ICC_DATE_CLASSES ICC_LISTVIEW_CLASSES ICC_PROGRESS_CLASS ICC_TAB_CLASSES ICC_TREEVIEW_CLASSES ICC_UPDOWN_CLASS

Similarly, the prior probability of bad weather can be looked up from meteorological data, which shows that 20% of the time bad weather occurs (to ne-tune the system, we could adjust this probability to re ect the time of year we would expect, for example, that bad weather is more likely to occur during the winter than during the summer) The conditional probabilities are more dif cult to determine For instance, P(P1|M1,B1) is the probability that a plane is late, given that there is both mechanical failure and bad weather This data may be determined from the historical record If, however, these data are not readily available, or very dif cult.

Computing quotients of polynomials, and more importantly, the remainder after &vision, plays a significant role in encoding cyclic codes. The circuits of this section will be applied to that end. Figure 4.5 illustrates a device for computing the quotient and remainder of the polyno-

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In this case, the access zones may be operated by other parties than the core network Also the use of Mobile IP in cellular systems has been analysed using example scenarios (see [FLP04])..

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