Dynamic probability route optimization for connection handoff in LEO networks

In LEO networks, the connections need to be rerouted after connection handoff as mobile users move among footprint of the satellites. The rerouting of the connections must be done quickly enough to produce the minimal disruption to traffic. In addition, the resulted routes must be optimal. A reasonable approach is to implement handoff in two phases. In the first phase connections are rapidly rerouted and in the second phase a route optimization procedure is executed. The route optimization should impose minimal signaling and processing load on the satellite nodes. To implement the two-phase handoff protocol efficiently, we need to determine when trigger path optimization. In this paper, we propose and study a dynamic probability execution of route optimization for a two-phase handoff scheme. The design objective of proposed scheme is to determine the time to invoke path optimization such that the average cost per call is minimized. An analytical and simulation model is developed to study the performance of our scheme. The dynamic probability route optimization scheme is shown to minimize signaling and processing load while maximizing utilization of network resources.