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Energy Efficient Sleep Scheduling for Wireless Sensor Networks

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9528))

Abstract

Recently, wireless sensor network (WSN) has become a formidable force in almost all areas of our everyday life. However, there are still many issues with wireless sensor networks among which is the energy problem. One of the numerous techniques that have been introduced as a way of solving the problem of energy deficit inherent in a WSN is sleep scheduling. Sleep scheduling allows sensor nodes to periodically take turns to sleep in order to minimize energy cost in a WSN. Apparently, Overemission in a WSN is one of the main causes of energy drainage in sensor nodes. Traditional schemes fail to take into consideration the sleeping timetable of other nodes; hence they let transmitter nodes repeatedly send RTS preamble packets and similar control packets to sleeping nodes. Our proposed sleep scheduling scheme addresses this problem from a whole new perspective using a system called Designated Sensor Node (DSN) mechanism. The DSN scheme significantly reduces flooding of the network with unnecessary control packets. The effect in turn leads to the minimization of unnecessary energy waste in a WSN.

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Acknowledgments

This research was financially supported by the Ministry of Education (MOE) and National Research Foundation of Korea (NRF) through the Human Resource Training Project for Regional Innovation (no. 2014H1C1A1067126), the BK21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by the Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005), and the This work was supported by the IT R&D program of MSIP/KEIT. [10041145, Self-Organized Software platform (SoSp) for Welfare Devices].

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Correspondence to Kijun Han .

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© 2015 Springer International Publishing Switzerland

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Uzoh, P.C., Li, J., Cao, Z., Kim, J., Nadeem, A., Han, K. (2015). Energy Efficient Sleep Scheduling for Wireless Sensor Networks. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9528. Springer, Cham. https://doi.org/10.1007/978-3-319-27119-4_30

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  • DOI: https://doi.org/10.1007/978-3-319-27119-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27118-7

  • Online ISBN: 978-3-319-27119-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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