Abstract
We consider the problem of data collection from a continental-scale network of mobile sensors, specifically applied to wildlife tracking. Our application constraints favor a highly asymmetric solution, with heavily duty-cycled sensor nodes communicating with a network of powered base stations. Individual nodes move freely in the environment, resulting in low-quality radio links and hot-spot arrival patterns with the available data exceeding the radio link capacity. We propose a novel scheduling algorithm, κ-Fair Scheduling Optimization Model (κ-FSOM), that maximizes the amount of collected data under the constraints of radio link quality and energy, while ensuring a fair access to the radio channel. We show the problem is NP-complete and propose a heuristic to approximate the optimal scheduling solution in polynomial time. We use empirical link quality data to evaluate the κ-FSOM heuristic in a realistic setting and compare its performance to other heuristics. We show that κ-FSOM heuristic achieves high data reception rates, under different fairness and node lifetime constraints.
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Li, K., Kusy, B., Jurdak, R., Ignjatovic, A., Kanhere, S.S., Jha, S. (2014). κ-FSOM: Fair Link Scheduling Optimization for Energy-Aware Data Collection in Mobile Sensor Networks. In: Krishnamachari, B., Murphy, A.L., Trigoni, N. (eds) Wireless Sensor Networks. EWSN 2014. Lecture Notes in Computer Science, vol 8354. Springer, Cham. https://doi.org/10.1007/978-3-319-04651-8_2
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DOI: https://doi.org/10.1007/978-3-319-04651-8_2
Publisher Name: Springer, Cham
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