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We study a wireless ad-hoc sensor network (WASN) where N sensors gather data from the surrounding environment and transmit their sensed information to M fusion centers (FCs) via multi-hop wireless communications. This node deployment problem is formulated as an optimization problem to make a trade-off between the sensing uncertainty and energy consumption of the network. Our primary goal is to find an optimal deployment of sensors and FCs that minimizes a Lagrangian combination of sensing uncertainty and energy consumption. To support arbitrary routing protocols in WASNs, the routing dependent necessary conditions for the optimal deployment are explored. Based on these necessary conditions, we propose a routing-aware Lloyd-like algorithm to optimize node deployment. Simulation results show that our proposed algorithm outperforms the existing deployment algorithms, on average.
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Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks
We study a heterogeneous two-tier wireless sensor network in which N heterogeneous access points (APs) collect sensing data from densely distributed sensors and then forward the data to M heterogeneous fusion centers (FCs). This heterogeneous node deployment problem is modeled as a quantization problem with distortion defined as the total power consumption of the network. The necessary conditions of the optimal AP and FC node deployment are explored in this paper. We provide a variation of Voronoi diagrams as the optimal cell partition for this network, and show that each AP should be placed between its connected FC and the geometric center of its cell partition. In addition, we propose a heterogeneous two-tier Lloyd-like algorithm to optimize the node deployment. Simulation results show that our proposed algorithm outperforms the existing methods like Minimum Energy Routing, Agglomerative Clustering, and Divisive Clustering, on average.
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- Award ID(s):
- 1815339
- PAR ID:
- 10108983
- Date Published:
- Journal Name:
- IEEE International Symposium on Information Theory (ISIT-19)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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