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An image processing inspired mobile sink solution for energy efficient data gathering in wireless sensor networks

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Abstract

This paper presents a gradient-based multi-hop clustering protocol combined with a mobile sink (MS) solution for efficient data gathering in wireless sensor networks. The main insight for the clustering algorithm is drawn from image processing field and namely from the watershed transform, widely used for image segmentation. The proposed algorithm creates multi-hop clusters whose cluster heads (CHs) as well as cluster members near the CHs have high energy reserves. Specifically, the energy of the sensors in a cluster increases progressively as getting closer to the CH. As the nodes closer to the CH are most burdened with relaying of data from other cluster members, the higher levels of available energy at these nodes prolong the network lifetime eventually. After cluster formation, a MS periodically visits each CH and collects the data from cluster members already gathered at the CH. Simulation results show the higher performance of the proposed scheme in comparison to other competent approaches in the literature.

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Notes

  1. Similar behavior (and corresponding differences in favor of our clustering-based data gathering protocol) is observed for the other numbers of sensor nodes too, for all the three protocols.

  2. Note also here that the energy consumed during the local and global re-clustering procedures required in our data gathering scheme has been included in all the corresponding measurements.

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Acknowledgments

This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program: Archimedes III. Investing in knowledge society through the European Social Fund.

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Authors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Charalampos Konstantopoulos

  2. Department of Informatics, Technological Educational Institute of Athens, Athens, Greece

    Basilis Mamalis, Grammati Pantziou & Vasileios Thanasias

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  1. Charalampos Konstantopoulos
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  2. Basilis Mamalis
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  3. Grammati Pantziou
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  4. Vasileios Thanasias
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Correspondence to Basilis Mamalis.

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Konstantopoulos, C., Mamalis, B., Pantziou, G. et al. An image processing inspired mobile sink solution for energy efficient data gathering in wireless sensor networks. Wireless Netw 21, 227–249 (2015). https://doi.org/10.1007/s11276-014-0779-x

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