Distributed situation-aware scheduling algorithm for network navigation

Wang, Tianheng; Teague, Bryan; Win, Moe Z.

doi:10.1109/icuwb.2017.8250974

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…i . Equations (23) and (26) indicate that b(x (n) i ) can be obtained via an update step (cf. (8)) followed by marginalization.…”

Section: B Distributed Network Localization Algorithmsmentioning

confidence: 99%

“…Note that sigma point belief propagation (SPBP) [5] and the network localization algorithm in [6] have been developed according to Steps 1-3. [26] is an indispensable part for localization in the IoT. The network operation strategies presented in this paper focus on the coordination of measurements provided by range measurement units (RMUs), i.e., the measurement model in (15) is…”

Section: B Distributed Network Localization Algorithmsmentioning

confidence: 99%

“…where the expectation in the objective function is over the randomness in the channel access event for all the agents. It can be shown [26] that the optimal channel access probabilities ζ…”

Section: A Node Activationmentioning

confidence: 99%

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Efficient Multisensor Localization for the Internet of Things: Exploring a New Class of Scalable Localization Algorithms

Win

Meyer

Liu

et al. 2018

IEEE Signal Process. Mag.

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130

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In the era of the Internet-of-Things (IoT), efficient localization is essential for emerging mass-market services and applications. IoT devices are heterogeneous in signaling, sensing, and mobility as well as their resources for computation and communication are typically limited. Therefore, to enable location-awareness in large-scale IoT networks, there is a need for efficient, scalable, and distributed multi-sensor fusion algorithms. This paper presents a framework to design network localization and navigation (NLN) for IoT. Multi-sensor localization and operation algorithms developed within NLN can exploit spatiotemporal cooperation, are suitable for arbitrary large network sizes, and only rely on an information exchange among neighboring devices. The advantages of NLN are evaluated in a large-scale IoT network with five hundreds agents. In particular, it is demonstrated that due to multi-sensor fusion and cooperation, the presented network localization and operation algorithms can provide attractive localization performance and reduce communication overhead and energy consumption.

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“…i . Equations (23) and (26) indicate that b(x (n) i ) can be obtained via an update step (cf. (8)) followed by marginalization.…”

Section: B Distributed Network Localization Algorithmsmentioning

confidence: 99%