Network navigation is a promising paradigm for enabling location awareness in dynamic wireless networks. A wireless navigation network consists of agents (mobile with unknown locations) and anchors (possibly mobile with known locations). Agents can estimate their locations based on inter- and intra-node measurements as well as prior knowledge. With limited wireless resources, the key to achieve high navigation accuracy is to maximize the benefits of agents’ channel usage. Therefore, it is critical to design scheduling algorithms that adaptively determine with whom and when an agent should perform inter-node measurements to achieve both high navigation accuracy and efficient channel usage. This paper develops a framework for the design of distributed scheduling algorithms in asynchronous wireless navigation networks, under which the algorithm parameters are optimized based on the evolution of agents’ localization errors. Results show that the proposed algorithms lead to high-accuracy, efficient, and flexible network navigation.

Network navigation with scheduling: Distributed algorithms

Conti A.
Secondo
;
2019

Abstract

Network navigation is a promising paradigm for enabling location awareness in dynamic wireless networks. A wireless navigation network consists of agents (mobile with unknown locations) and anchors (possibly mobile with known locations). Agents can estimate their locations based on inter- and intra-node measurements as well as prior knowledge. With limited wireless resources, the key to achieve high navigation accuracy is to maximize the benefits of agents’ channel usage. Therefore, it is critical to design scheduling algorithms that adaptively determine with whom and when an agent should perform inter-node measurements to achieve both high navigation accuracy and efficient channel usage. This paper develops a framework for the design of distributed scheduling algorithms in asynchronous wireless navigation networks, under which the algorithm parameters are optimized based on the evolution of agents’ localization errors. Results show that the proposed algorithms lead to high-accuracy, efficient, and flexible network navigation.
2019
Wang, T.; Conti, A.; Win, M. Z.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2417521
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