Title :
Exponential random geometric graph process models for mobile wireless networks
Author_Institution :
Dept. of Math., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
In this paper, we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential first order autoregressive (AR(1)) process. The transition probability matrix and stationary distribution are derived for the Markov chains in terms of network connectivity and the number of components. We characterize an algorithm for the hitting time regarding disconnectivity. In addition, we also study static topological properties including connectivity, degree distributions and the largest nearest neighbor distance associated with the random graph process. Both closed form results and limit theorems are provided.
Keywords :
Markov processes; radio networks; 1D random geometric graph process; Markov chains; disconnectivity; exponential first order autoregressive process; exponential random geometric graph process model; inter-nodal gaps; mobile wireless networks; nearest neighbor distance; network connectivity; random graph process; stationary distribution; transition probability matrix; Analytical models; Autoregressive processes; Joining processes; Mathematical model; Mathematics; Nearest neighbor searches; Probability distribution; Solid modeling; Wireless networks; Wireless sensor networks; autoregressive process; component; connectivity; mobile network; random geometric graph;
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009. CyberC '09. International Conference on
Conference_Location :
Zhangijajie
Print_ISBN :
978-1-4244-5218-7
Electronic_ISBN :
978-1-4244-5219-4
DOI :
10.1109/CYBERC.2009.5342212
