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A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks

A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks

Oliver Stecklina, Peter Langendörfer, Christian Goltz
Copyright: © 2013 |Volume: 9 |Issue: 4 |Pages: 22
ISSN: 1548-0631|EISSN: 1548-064X|EISBN13: 9781466634961|DOI: 10.4018/ijbdcn.2013100101
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MLA

Stecklina, Oliver, et al. "A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks." IJBDCN vol.9, no.4 2013: pp.1-22. http://doi.org/10.4018/ijbdcn.2013100101

APA

Stecklina, O., Langendörfer, P., & Goltz, C. (2013). A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks. International Journal of Business Data Communications and Networking (IJBDCN), 9(4), 1-22. http://doi.org/10.4018/ijbdcn.2013100101

Chicago

Stecklina, Oliver, Peter Langendörfer, and Christian Goltz. "A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks," International Journal of Business Data Communications and Networking (IJBDCN) 9, no.4: 1-22. http://doi.org/10.4018/ijbdcn.2013100101

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Abstract

Wireless sensor nodes become more and more attractive for a broad variety of application scenarios. Wireless Sensor Networks (WSNs) can be easily deployed and they require by design low maintenance effort. But running installations are still rare, because real world requirements and environmental conditions are even today a big challenge. Especially in multi-hop networks a minimum lifetime of several years cannot be achieved globally. In this paper, the authors present a Distributed Low Duty Cycle (DLDC) based Multi-Hop Routing (MHR) protocol for Wireless Sensor Networks guaranteeing a minimum network lifetime. The authors introduce a forecast scheme to calculate the expected life of a node with a minimal effort. The authors are convinced that by using a forecast scheme the network topology and the used protocols can be easily optimized before deploying the network. The authors evaluated their forecast scheme by measuring real sensor node parameters and simulating an example network in the Castalia simulation framework. The authors demonstrated that by using the proposed scheme an energy consumption forecast with a deviation of less than three per cent can be achieved.

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