a new distributed dynamic algorithm for mobility patterns prediction
Deployment of future ALL-IP mobile communication networks requires overcoming many challenges. One of them is how to provide QoS guarantee in such high dynamic environments. Basic principle is to couple between mobility and QoS solutions, so that handoffs are executed and simultaneously resources reserved. Most approaches doing such coupling optimize the performance by constructing neighbor groups to enable achieving in-advance actions accelerating the handoff as well as resources reservation. Optimizing the groups constructed based on Mobile Nodes' (MNs) mobility and traffic characteristics will result in an optimized performance and minimized network resources consumption. This paper proposes a new mechanism capable of achieving such an optimization. The new mechanism optimizes neighbor groups without requiring the storage of mobility patterns of individual MNs or forcing MNs to do lots of measurements. The basic idea is to extend the well-known Neighbor Graph (NG) to consider MNs' traffic and mobility characteristics. The extension lies in weighting the edges of the NG based on the services the network offers as well as movements patterns of MNs residing in the network. In such a way, each MN is associated with a neighbor group updated over the time based on the variation in its traffic characteristics. Our algorithm is fully distributed and highly improves the performance.
mobility patterns prediction qos neighbor graph mobility management