The coverage areas of cellular networks are logically subdivided into service areas. Each service area has a local anchor node which “hides” the mobility inside the area and the entire network has a global anchor node which “hides” the mobility between areas.

The concept of unique local anchor nodes per service area was invented to simplify routing but has been found to complicate expansion. The rapidly growing demand for cellular access has therefore prompted for alternative solutions with pools of local anchor nodes per service area. Such pools are now deployed by several operators all over the world.

Users in pooled service areas are mapped to specific pool members according to a load distribution policy, but the mapping can change as a result of node failures or operator interventions. Such changes take a certain time to implement and cause additional load on the anchor nodes. We study these processes in detail and derive closed form expressions which allow operators to control the trade-off between rapid changes and acceptable loads.

Finally we show that the key assumptions of our model are in agreement with measured data and demonstrate how the model can be applied to investigate the effects of different network settings (timers) under different user behaviour (traffic and mobility).

Contrary to current solutions to this problem, which typically are slow and/or inaccurate, our results enable fast and accurate analysis of different scenarios thereby enabling operators to maximise utilisation of the existing investments and at the same time avoid potentially dangerous situations of overload.