TY - CONF
SP - 368
UR - http://netys.net/history/netys2020/netys.net/index.html
AV - public
T2 - NETYS 2020. The 8th Edition of International Conference on NETworked Systems
ID - upm66058
VL - 12129
TI - Routing in Generalized Geometric Inhomogeneous Random Graphs
A1 - Sevilla De Pablo, Andres
A1 - Fernández Anta, Antonio
SN - 978-3-030-67087-0
N2 - In this paper we study a new random graph model that we denote (k, p)-KG and new greedy routing algorithms (of deterministic and probabilistic nature). The (k,p)-KG graphs have power-law degree distribution and small- world properties. (k,p)-KG roots on the Geometric Inhomogeneous Random Graph (GIRG) model, and hence they both preserve the properties of the hyperbolic graphs and avoid the problems of using hyperbolic cosines. In order to construct (k, p)-KG graphs, we introduce two parameters k and p in the process of building a (k,p)-KG graph. With these parameters we can generate Klein- berg and power-law networks as especial cases of (k, p)-KG. Also, we propose two new greedy routing algorithms to reduce the fail ratio and maintaining a good routing performance. The first algorithm is deterministic and the second is, in essence, a weighted random walk. We use simulation techniques to test our network model, and evaluate the new routing algorithms on the two graph models (GIRG and (k, p)-KG). In our simulations, we evaluate the number of hops to reach a destination from a source and the routing fail ratio, and measure the impact of the parameters (k and p) on the performance of the new routing algorithms. We observe that our graph model (k, p)-KG is more flexible than GIRG, and the new routing algorithms have better performance than the routing algorithms previously proposed.
M2 - Marrakech, Morocco
Y1 - 2020///
PB - Springer
EP - 373
ER -