Abstract
Wireless sensor networks will be responsible for the majority of the growth in smart building systems over the next decade. In resource constrained wireless sensor networks, it is very important to design the protocols with energy efficiency to prolong the lifetime of the sensor networks. Node clustering and data aggregation become popular since cluster-based sensor network can enhance the whole network throughput by aggregating the collected sensory information in each cluster. In such a network, the cluster head nodes play an important role in forwarding data originated from other common nodes to the sink. As a consequence, the cluster head nodes will have the problem of quick energy depletion upon multiple packets forwarding in high data load sensor networks. In this paper, we proposed a simple cluster-based linear network coding protocol in which random linear network coding is applied at cluster head nodes in order to minimize the number of forward packets to the sink. Simulation results are provided to show the efficacy of the proposed method in terms of the throughput and end-to-end delay.
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Acknowledgement
This research is funded by the Republic of Singapore’s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. BEARS has been established by the University of California, Berkeley as a center for intellectual excellence in research and education in Singapore.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Shwe, H.Y., Chong, P.H.J. (2015). Building Efficient Multi-level Wireless Sensor Networks with Clustering. In: Mumtaz, S., Rodriguez, J., Katz, M., Wang, C., Nascimento, A. (eds) Wireless Internet. WICON 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-319-18802-7_2
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DOI: https://doi.org/10.1007/978-3-319-18802-7_2
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