New tight upper bounds on the capacity for general deterministic dissemination in wireless ad hoc networks
2015
In this paper, we study capacity scaling laws of the deterministic dissemination (DD) in random wireless networks under the generalized physical model (GphyM). This is truly not a new topic. Our motivation to readdress this issue is two-fold: Firstly, we aim to propose a more general result to unify the network capacity for general homogeneous random models by investigating the impacts of different parameters of the system on the network capacity. Secondly, we target to close the open gaps between the upper and the lower bounds on the network capacity in the literature. We derive the general upper bounds on the capacity for the arbitrary case of (λ, nd, ns) by introducing the Poisson Boolean model of continuum percolation, where λ, nd, and ns are the general node density, the number of destinations for each session, and the number of sessions, respectively. We prove that the derived upper bounds are tight according to the existing general lower bounds constructed in the literature.
Keywords:
- Mathematical optimization
- Real-time computing
- Boolean model
- Wireless network
- Continuum percolation theory
- Percolation theory
- Computer science
- Distributed computing
- Scaling
- Wireless ad hoc network
- Stochastic geometry models of wireless networks
- Poisson distribution
- Computer network
- Theoretical computer science
- Topology
- random model
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