Distributed Routing Strategy Based on Machine Learning for LEO Satellite Network

On distributed, geographic-based packet routing for LEO satellite networks

Thomas R. Henderson Randy H. Katz Geo ast Network Systems, In . Ele tri al Engineering and Computer S ien e Dept. 190 Independen e Drive University of California, Berkeley Menlo Park, CA 94025 Berkeley, CA 94720 Abstra t|Advan es in satellite te hnology are enabling the deployment of large onstellations of Low-EarthOrbiting (LEO) satellites. Next-generation systems will be tailored for broadban...

Distributed on-demand routing for LEO satellite systems

Notwithstanding the limited commercial success of the first narrowband Low Earth Orbit (LEO) satellite systems, the interest of the scientific community in this type of systems has been revived on the basis of the current trend toward the migration to all IP-based services. LEO systems can play a pivotal role in providing services to areas where there is no substantial terrestrial infrastructur...

Agent-Based Distributed Routing Algorithm with Traffic Prediction for LEO Satellite Network

Satellite network, especially low earth orbit (LEO) satellite network, which has advantages of global coverage and short round-trip time (RTT), has played an increasingly important role in the future generation of global communication network. Due to fast velocity, frequent handover and time-varying topology, designing effective routing algorithm for LEO satellite network has always been challe...

Design of IP-based Routing in a LEO Satellite Network

Distributed Traffic Balancing Routing for LEO Satellite Networks

Satellite networks have been widely investigated both in the business and academia for many years, with many important routing algorithms reported in the literatures. However, fewer existing routing algorithms focus on the trade-off between the routing survivability and the routing computation and storage overheads. Due to topological dynamics, it is difficult to effectively apply the conventio...