“Density-aware Random Clustering in Ad-hoc Networks” by Doğanalp Ergenç

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Date/Time
Date(s) - 30/11/2017
4:00 pm - 5:30 pm

Location
IBM Lab

Categories


Abstract:
Clustering makes an ad hoc network scalable while increasing  control overhead. In this paper, we propose Random Clustering Algorithm that is a 
simple and efficient clustering algorithm with minimal overhead. In this algorithm, cluster heads are determined randomly in a distributed fashion.
An analytic model  is introduced for nodes to compute the probability of declaring themselves as cluster heads. We validate the analytic model by 
Monte-Carlo simulations. Furthermore, we propose a cross-layer clustered stack and  simulate simple applications in stationary and dynamic topologies 
using OMNeT++. Discrete event simulation results show that Random Clustering Algorithm eliminates a significant amount of control overhead and the 
performance of the algorithm is considerably better compared to its opponent, identity-based clustering.

Presentation,pdf