ubscriber network connections below the 'cloud'. Only ATM and TDM inter- faces are indicated for simplicity, but a typical MSG has a number of other interface possibilities like frame relay, Ethernet and IP/MPLS (multi-protocol label switching). The main components shown are MSGs and telephony servers with mediation logic (ML) and a MGW for switching signaling traffic, transit traffic (break in/break out to/from the area) and announcement machine traffic. The ML processor handles the gateway control communication, whereas the telephony server processor handles the normal 'horizontal' signalling. Within the cloud there might be a number of ATM core switches. The TDM voice traffic is transformed into ATM by the boards at the TDM interface. This transformation from one transfer mode to another one is called emulation (CE) and the boards are called circuit emulation boards. VOICE TRAFFIC VERSUS DATA TRAFFIC The behaviour of the voice traffic is well known, and dimensioning voice networks using Erlang tables is a routine task that operators do regularly. Voice calls are normally ran- domly distributed in arrival time, enabling statistical calculations (such as Erlang formulas) to be used. The time arrival distribution is called a Poisson distribution. The data traffic is more difficult to calculate and thus more rough estimates have to be done. The traffic is bursty with clustered arrivals. There might also be long range dependencies between the bursts. When carried in ATM we can use traffic expressions such as peak cell ratio (PCR) and average cell ratio (ACR) to measure the burstiness = PCR/ACR. Voice and data have almost totally different QoS requirements for the end-to-end trans- fer. See Chapters 3 and 7. Voice is delay sensitive and loss tolerant, whereas data is error/loss sensitive and delay tolerant. Since ATM technology is designed for both traffic types it will be used in this appendix. When we mix these two types of traffic in the same network, the dimensioning will of course become more complex than dimen