2 citations · 3 across the 18 of their papers we have counts for
6 papers · 1 filter
Efficient Rare-Event Simulation for Random Geometric Graphs via Importance Sampling
Sarat Moka, Christian Hirsch, Volker Schmidt +1
Random geometric graphs defined on Euclidean subspaces, also called Gilbert graphs, are widely used to model spatially embedded networks across various domains. In such graphs, nod…
Rare Events in Random Geometric Graphs
Christian Hirsch, Sarat B. Moka, Thomas Taimre +1
This work introduces and compares approaches for estimating rare-event probabilities related to the number of edges in the random geometric graph on a Poisson point process. In the…
Perfect Sampling for Gibbs Point Processes Using Partial Rejection Sampling
Sarat B. Moka, Dirk P. Kroese
We present a perfect sampling algorithm for Gibbs point processes, based on the partial rejection sampling of Guo et al. (2017). Our particular focus is on pairwise interaction pro…
Rejection and Importance Sampling based Perfect Simulation for Gibbs hard-sphere models
S. B. Moka, S. Juneja, M. R. H. Mandjes
Coupling from the past (CFTP) methods have been used to generate perfect samples from finite Gibbs hard-sphere models, an important class of spatial point processes, which is a set…
Diffusion Parameters of Flows in Stable Multi-class Queueing Networks
Sarat Babu Moka, Yoni Nazarathy, Werner Scheinhardt
We consider open multi-class queueing networks with general arrival processes, general processing time sequences and Bernoulli routing. The network is assumed to be operating under…
Regenerative Simulation for Queueing Networks with Exponential or Heavier Tail Arrival Distributions
Sarat Babu Moka, Sandeep Juneja
Multiclass open queueing networks find wide applications in communication, computer and fabrication networks. Often one is interested in steady-state performance measures associate…