Hidden issues in the simulation of fixed wireless systems
Wireless Networks
The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Effect of overhearing transmissions on energy efficiency in dense sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Toward Quasiregular Sensor Networks: Topology Control Algorithms for Improved Energy Efficiency
IEEE Transactions on Parallel and Distributed Systems
NPART - node placement algorithm for realistic topologies in wireless multihop network simulation
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Scalable target coverage in smart camera networks
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Target-oriented coverage maximization in visual sensor networks
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
SAGA: socially- and geography-aware mobility modeling framework
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Coverage algorithms for visual sensor networks
ACM Transactions on Sensor Networks (TOSN)
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Most analysis and simulation of wireless systems assumes that the nodes are randomly located, sampled from a uniform distribution. Although in many real-world scenarios the nodes are non-uniformly distributed, the research community lacks a common approach to generate such inhomogeneities. This paper intends to go a step in this direction. We present an algorithm to create a random inhomogeneous node distribution based on a simple neighborhood-dependent thinning of a homogeneous Poisson process. We derive some useful stochastic properties of the resulting distribution (in particular the probability density of the nearest neighbor distance) and offer a reference implementation. Our goal is to enable fellow researchers to easily use inhomogeneous distributions with well-defined stochastic properties.