Abstract
Recently a lot of research effort has been focused on Wireless Sensor Networks (WSNs) due to its various applications. Over the last few years, several techniques have been proposed for investigating the power consumption which represents one of the most challenges and main concerns in designing WSNs. Power consumption of nodes in WSNs has a great effect on the lifetime of network nodes which are difficult to replace or recharge their batteries. In this context, this paper represents a receiver approach for alleviating power consumption of WSNs. Unlike other power consumption techniques, instead of decoding every received signal at the receiver which consume too much power our approach studies the histograms of sensors’ transmitted signals to detect collisions, so the receiver can determine when the transmitted signals can be decoded without wasting precious power decoding transmitted signals suffering from collisions. We also present a complexity and power-saving comparison between our novel approach and a conventional full-decoding algorithm in order to demonstrate the significant power and complexity saving advantage of our approach.
Keywords
- Efficient techniques in WSNs
- Low computational complexity algorithms
- Packets collision
- Power consumption techniques
- Signal statistics in WSNs
- WSNs protocols
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Notes
- 1.
For the remainder of this paper, we shall refer to our proposed approach as the “Statistical Discriminator, or SD” method. We shall also refer to the traditional full-decoding methods as “FD” methods.
- 2.
The actual design details and choice of the multiple access mechanism, e.g., slotted or un-slotted Aloha, are beyond the scope of this paper and irrelevant to the specifics of the techniques proposed herein.
- 3.
Our system throughput is defined as \( Throughput={\left(1-{P}_{FA}\right)}_{SD} \); Where P FA denotes the False-Alarm probability.
- 4.
The measurement period is 50 bits and the modulation scheme is QPSK, so the number of symbols is 25.
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Acknowledgment
This work has been partially sponsored by Stevens Institute of Technology, Hoboken, NJ, USA and Taif University of the Kingdom of Saudi Arabia. Some of this work has been presented in part at The World Congress on Engineering, 2–4 July, 2014, London, U.K. [16].
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Alassery, F., Ahmed, W., Sarraf, M., Lawrence, V. (2015). Fast Power-Efficient Techniques for Collision Detection in Wireless Sensor Networks. In: Yang, GC., Ao, SI., Gelman, L. (eds) Transactions on Engineering Technologies. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9804-4_36
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DOI: https://doi.org/10.1007/978-94-017-9804-4_36
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