Predictive Models for Load Reduction in Wireless Sensor Networks
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-0901-6_39
Reference18 articles.
1. van Renesse R (2003) The importance of aggregation. In: Schiper A, Shvartsman AA, Weatherspoon H, Zhao BY (eds) Future directions in distributed computing. Lecture notes in computer science, vol 2584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-37795-6_16
2. Chauhan AA, Udgata SK (2021) Load reduction using temporal modeling and prediction in periodic sensor networks. In: Udgata SK, Sethi S, Srirama SN (eds) Intelligent systems. Lecture notes in networks and systems, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-33-6081-5_20
3. Anastasi G, Conti M et al (2009) Energy conservation in wireless sensor networks: a survey. Adhoc Netw 7(3):537–568. https://doi.org/10.1016/j.adhoc.2008.06.003
4. Zhang H, Zhang X, Sung DK (2015) Lightweight self-adapting linear prediction algorithms for wireless sensor networks. IEEE Sens J 15(5):3050–3058. https://doi.org/10.1109/JSEN.2014.2385854
5. Li G, Wang Y (2013) Automatic ARIMA modeling-based data aggregation scheme in wireless sensor networks. J Wireless Com Netw 2013:85. https://doi.org/10.1186/1687-1499-2013-85
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