A fast, adaptive, and energy-efficient multi-path-multi-channel data collection protocol for wireless sensor networks

Tan, Cheng Kiat and Liew, Soung Yue and Goh, Hock Guan and Andonovic, Ivan; (2017) A fast, adaptive, and energy-efficient multi-path-multi-channel data collection protocol for wireless sensor networks. In: Proceedings - 2017 International Conference on Recent Advances in Signal Processing, Telecommunications and Computing, SigTelCom 2016. Institute of Electrical and Electronics Engineers Inc., VNM, pp. 33-38. ISBN 978-1-5090-2292-2 (https://doi.org/10.1109/SIGTELCOM.2017.7849791)

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Abstract

Energy consumption, traffic adaptability, fast data collection, etc are the major issues in wireless sensor networks (WSNs). Most existing WSN protocols are able to handle one or two of the above issues with the other(s) being compromised. In order to reduce the energy consumption of wireless sensor nodes while having fast data collection under different traffic generating rates, this paper proposes a fast, adaptive, and energy-efficient multi-path-multi-channel (FAEM) data collection protocol. FAEM makes use of the Basketball Net Topology proposed in the literature, in which a multi-parent-multi-child connection table is pre-established at each node; each node is also pre-assigned a receiving channel which is different from those of the neighboring nodes so as to eliminate the transmission interference. During data transmission, time is divided into duty cycles, and each consists of two phases, namely distributed iterative scheduling phase and slot-based packet forwarding phase. The former is to match parents and children of the entire WSN in a distributed manner in order to determine whether a node should be in upload (to which parent), download (from which child), or sleep mode in a particular slot; while the latter is for nodes to take action according to the schedule. Simulation shows that our protocol is able to achieve lower energy consumption, data reliability and low latency even during a high traffic load.