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Energy-efficient scheduling strategies for minimizing big data collection in cluster-based sensor networks

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Abstract

Today, wireless sensor networks (WSNs) have been widely used in monitoring various applications, such as environment, military and health-care, etc. The explosive growth of the data volume generated in these applications has led to one of the most challenging research issues of the big data era. To deal with such amounts of data, exploring data correlation and scheduling strategies have received great attention in WSNs. In this paper, we propose an efficient mechanism based on the Euclidean distance for searching the spatial-temporal correlation between sensor nodes in periodic applications. Based on this correlation, we propose two sleep/active strategies for scheduling sensors in the network. The first one searches the minimum number of active sensors based on the set covering problem while the second one takes advantages from the correlation degree and the residual energy of the sensors for scheduling them in the network. Our mechanism with the proposed strategies were successfully tested on real sensor data. Compared to other existing techniques, the simulation results show that our mechanism significantly extends the lifetime of the network while conserving the quality of the collected data and the coverage of the monitored area.

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Notes

  1. The values 0 and 1 of the sensor mean that it can be on sleep or active mode respectively.

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Acknowledgments

This project has been performed in cooperation with the Labex ACTION program (contract ANR-11-LABX-0001-01).

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Sciences, American University of Culture and Education (AUCE), Beirut, Lebanon

    Hassan Harb

  2. FEMTO-ST Institute/CNRS, the DISC Department, University Bourgogne Franche-Comté, Belfort, France

    Abdallah Makhoul

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  1. Hassan Harb
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  2. Abdallah Makhoul
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Correspondence to Hassan Harb.

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The authors declare that they have no conflict of interest.

Additional information

This article is part of the Topical Collection: Special Issue on Network Coverage

Guest Editors: Shibo He, Dong-Hoon Shin, and Yuanchao Shu

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Harb, H., Makhoul, A. Energy-efficient scheduling strategies for minimizing big data collection in cluster-based sensor networks. Peer-to-Peer Netw. Appl. 12, 620–634 (2019). https://doi.org/10.1007/s12083-018-0639-z

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  • DOI: https://doi.org/10.1007/s12083-018-0639-z

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