Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Analytical modeling and mitigation techniques for the energy hole problem in sensor networks
Pervasive and Mobile Computing
Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution
IEEE Transactions on Parallel and Distributed Systems
On the design of heterogeneous sensor networks based on small world concepts
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution
IEEE Transactions on Mobile Computing
Geometry and random graphs for the analysis and design of wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
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Node deployment plays an important role in the design of wireless sensor networks (WSNs). Many important properties such as coverage, connectivity, data fidelity, lifetime and fault tolerance are influenced by the way nodes are placed in the sensor field. In this work we argue that topological information is able to characterize network properties and, once estimated, it can be used in their design in order to improve performance. In this context, we propose a stochastic point process model, namely M2P2, which aims at describing a wide variety of WSN deployment strategies and a topological metric, namely Sink Betweenness, suitable for characterizing the relay task of a node.